• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.385-391
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• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.

• Journal of Environmental Impact Assessment
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• v.25 no.6
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• pp.514-524
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• 2016

The Bio-Climatic impact Assessment System, BioCAS was utilized to produce analysis maps of daily maximum perceived temperature ($PT_{max}$) and excess mortality ($r_{EM}$) over the entire Seoul area on a heat wave event. The spatial resolution was 25 m and the Aug. 5, 2012 was the selected heat event date. The analyzed results were evaluated by comparing with observed health impact data - mortality and morbidity - during heat waves in 2004-2013 and 2006-2011,respectively. They were aggregated for 25 districts in Seoul. Spatial resolution of the comparison was equalized to district to match the lower data resolution of mortality and morbidity. Spatial maximum, minimum, average, and total of $PT_{max}$ and $r_{EM}$ were generated and correlated to the health impact data of mortality and morbidity. Correlation results show that the spatial averages of $PT_{max}$ and $r_{EM}$ were not able to explain the observed health impact. Instead, spatial minimum and maximum of $PT_{max}$ were correlated with mortality (r=0.53) and morbidity (r=0.42),respectively. Spatial maximum of $PT_{max}$, determined by building density, affected increasing morbidity at daytime by heat-related diseases such as sunstroke, whereas spatial minimum, determined by vegetation, affected decreasing mortality at nighttime by reducing heat stress. On the other hand, spatial maximum of $r_{EM}$ was correlated with morbidity (r=0.52) but not with mortality. It may have been affected by the limit of district-level irregularity such as difference in base-line heat vulnerability due to the age structure of the population. Areal distribution of the heat impact by local building and vegetation, such as spatial maximum and minimum, was more important than spatial mean. Such high resolution analyses are able to produce quantitative results in health impact and can also be used for economic analyses of localized urban development.

• Journal of Bio-Environment Control
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• v.18 no.3
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• pp.177-184
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• 2009

For the purpose of reducing the cost for greenhouse operation by acquiring the electric power necessary for it, this study installed a solar photovoltaic system on the roof of the building adjacent to green-houses and experimentally examined the quantity of power generation based on weather conditions. The results of the study are as per the below: The maximum, average and minimum temperature while the experiment was conducted was $0.4{\sim}34.1,\;-6.1{\sim}22.2$, and $-14.1{\sim}16.7^{\circ}C$ respectively, and the solar radiation was $28.8MJ{\cdot}m^{-2}$ (maximum), $14.9MJ{\cdot}m^{-2}$ (average), and $0.6MJ{\cdot}m^{-2}$ (minimum). The quantity of electric power didn't increase in proportion to the quantity of solar radiation and instead, it was almost consistent around 750W. Daily maximum, average and minimum consumption of electric power was 5.2kWh, 2.5kWh and 0kWh respectively. Based on the average electric power consumption of the system used for this experiment, it was sufficient in case the capacity and the working time of a hot blast heater are small, but it was short in case they are big. In case the capacity of the hot blast heater is big, the average electric power quantity will be sufficient for array area $21m^2$, about three times of the present area. In summer when the temperature of the array becomes high, the generation of electric power didn't increase in proportion to the quantity of solar radiation, but this experiment result shows a high correlation between two factors (coefficient of correlation 0.84).

• Asian-Australasian Journal of Animal Sciences
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• v.20 no.6
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• pp.939-943
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• 2007

Two experiments were conducted to determine the lysine requirement of straight-run broiler chickens ($Hubbard{\times}Hubbard$) during the period 4-21 (Exp. 1) and 21-40 (Exp. 2) days of age. Experiments were conducted during the summer months (June-August) in open-sided houses, thus exposing chicks to chronic heat stress. Daily min-max temperature averaged $28-40^{\circ}C$ (Exp. 1) and $28-36^{\circ}C$ (Exp. 2). Lysine deficient basal diets were formulated to contain low-nutrient-density, i.e., 2,700 kcal per kg ME, 18.6% CP (Exp. 1), and 2,750 kcal per kg ME, 17.1% CP (Exp. 2), to mimic typical commercial broiler diets used in Pakistan. Diets were supplemented with L-lysine HCl to provide total lysine level ranging from 0.85 to 1.10% (six increments) and 0.72 to 1.02% (six increments), respectively in Exp. 1 and 2. Live performance data were subjected to quadratic analysis and requirement was defined as the level achieving 95% of maximum or minimum values. Lysine requirements were found to be 0.98 and 0.97% total lysine, respectively, for gain and feed efficiency during 4-21 days, and 0.87% total lysine for both gain and feed efficiency during 21-40 days of age. Calculated on a digestible lysine basis, the estimates were 0.85 and 0.84%, respectively, for gain and feed efficiency during 4-21 days of age; and 0.75% for gain and feed efficiency during 21-40 days of age.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.417-426
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• 2017

It is important to predict the flowering dates of Japanese cherry and autumnal dates in Korea. Flowering date is decided by heating requirement with daily maximum and minimum temperature used to calculate the pre-determined heating requirements for flowering. Recent, changes in climate have impacted the flowering season of Japanese cherry in Korea. When compared with the current normal, the flowering of Japanese cherry is expected to be about 10 days earlier than in near future normal years. In this paper, we first consider a linear model based on meteorological data that predicts the flowering date and then incorporate a spatial structure into the model. Real data analysis indicates that the proposed approach provides more reasonable predicted dates.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.61-72
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• 2017

Due to the climate change, damages of human life and property caused by natural disaster have recently been increasing consistently. In South Korea, total damage by natural disasters over 20 years from 1994 to 2013 is about 1.0 million dollars. The 13% of total damage caused by heavy snow. This is smaller amount than the damage by heavy rainfall or typhoon, but still could cause severe damage in the society. In this study, the snow damage in Gangwon region was estimated using climate variables (daily maximum snow depth, relative humidity, minimum temperature) and scoio-economic variables (Farm population density, GRDP). Multiple regression analysis with enter method was applied to estimate snow damage. As the results, adjusted R-square is above 0.7 in some sub-regions and shows the good applicability although the extreme values are not predicted well. The developed model might be applied for the prompt disaster response.

• Journal of The Korean Society of Grassland and Forage Science
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• v.39 no.2
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• pp.105-113
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• 2019

A two-year study was conducted from 2017 to 2018 by the establishment of a test field at Chungju-si and Cheongyang-gun. Plant height, number of leaves, insects and diseases, and fresh and dry matter yields for corn hybrid('Kwangpyeongok') were investigated. Daily average, maximum, and minimum temperature, monthly average temperature, daily precipitation, and sunshine duration during the growing season were investigated. We selected climate-critical factors to corn productivity and conducted an evaluation of vulnerability to climate change from 1999 to 2018 for both regions. In 2018, the dry matter yield of forage corn was 6,475 and 7,511 kg/ha in Chungju and Cheongyang, respectively, which was half of that in 2017. The high temperature and drought phenomenon in the 2018 summer caused the corn yield to be low. As well as temperature, precipitation is an important climatic factor in corn production. As a result of climate impact vulnerability assessment, the vulnerability has increased recently compared to the past. It is anticipated that if the high temperature phenomenon and drought caused by climate change continues, a damage in corn production will occur.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.3
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• pp.58-69
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• 2007

The vegetation area that occupies 76% in land surface of the earth can give a considerable impact on water resources, environment and ecological system by future climate change. The purpose of this study is to predict future vegetation cover information from NDVI (Normalized Difference Vegetation Index) extracted from satellite images. Current vegetation information was prepared from monthly NDVI (March to November) extracted from NOAA AVHRR (1994 - 2004) and Terra MODIS (2000 - 2004) satellite images. The NDVI values of MODIS for 5 years were 20% higher than those of NOAA. The interrelation between NDVIs and monthly averaged climate factors (daily mean, maximum and minimum temperature, rainfall, sunshine hour, wind velocity, and relative humidity) for 5 river basins of South Korea showed that the monthly NDVIs had high relationship with monthly averaged temperature. By linear regression, the future NDVIs were estimated using the future mean temperature of CCCma CGCM2 A2 and B2 climate change scenario. The future vegetation information by NOAA NDVI showed little difference in peak value of NDVI, but the peak time was shifted from July to August and maintained high NDVIs to October while the present NDVI decrease from September. The future MODIS NDVIs showed about 5% increase comparing with the present NDVIs from July to August.

• Korean Journal of Environmental Biology
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• v.28 no.1
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• pp.30-39
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• 2010

We researched community structure, species composition, and habitat environment of Dendropanax morbifera populations distributed in Goheung, Haenam, Wando (I.), and Bogildo (I.) at south coast of the Korean Peninsula. Our research was also estimated possible area for growth of Dendropanax morbifera by analyzing meteorological factors of the habitat thereof. Dendropanax morbifera community divided into Castanopsis cuspidata var. sieboldii group and Carpinus laxiflora group by difference of species composition. Broad-leaved evergreens showed high dominance value in view of rNCD in Dendropanax morbifera community as follows: Camellia japonica (100.0), Quercus acuta (88.6), Castanopsis cuspidata var. sieboldii (55.8), Dendropanax morbifera Lev. (41.4), Trachelospermum asiaticum var. intermedium (23.8), Eurya japonica (19.9) and Ligustrum japonicum (11.5). In the population distribution, 94.2% of Carpinus laxiflora group consisted of sapling and small size class that are less than 5 cm in DBH while 54.2% of Castanopsis cuspidata var. sieboldii group did. The soil environment of habitat showed low soil acidity, good organic matter and water content, and good drainage. The distribution area of Dendropanax morifera habitat had $13^{\circ}C$ or more in annual mean temperature, $7.4^{\circ}C$ or more in daily minimum temperature, $100^{\circ}C$ month or more in warmth index, and approximately 1,344 mm in mean annual precipitation. Dendropanax morifera habitat corresponded to evergreen broad-leaved forest zone located in islands and coast in the southwest region of the Korean Peninsula. The northern limit line of Dendropanax morifera community was determined as Gunsan-Jeongeup-Gwangju-Jinju-Pohang-Youngdeok line based on $13^{\circ}C$ in annual mean temperature that was confirmed in natural habitat of Dendropanax morifera community.

• Korean Journal of Plant Resources
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• v.27 no.2
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• pp.188-193
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• 2014

The sap outflow characteristics of Juglans sinensis and J. mandshurica were investigated to evaluate the optimum pruning period of walnut tree that there is a sap spill on dormant. The total period of sap outflow were 34 days for both J. sinensis and J. mandshurica. Total amount of sap outflow per tree in J. sinensis and J. mandshurica were 2,922 mL/tree and 3,135 mL/tree, respectively and the period of sap outflow and non sap outflow between two species were similar. ANOVA analysis showed that the amount of sap outflow was significant differences with day of sap outflow but there were no significant differences between species. From the correlation analysis between air-temperature and sap outflow, daily minimum temperature showed a positive correlation at the 1% level of significance (r=0.56 and r=0.46) for both J. sinensis and J. mandshurica. When branch of walnut tree that diameter is 5 cm cut on the period of sap outflow, the sap flowed down the longest period (48 days) but the sap outflow was not observed after budburst. Therefore, our study supported that the pruning have to avoid the period of sap outflow to reduce sap outflow of walnut tree.