• Journal of Climate Change Research
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• v.1 no.3
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• pp.189-203
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• 2010

The objective of this study is the estimate of $CO_2$ emissions by the energy consumption of functional technology introduced by classifying energy use in households according to functions as well as energy resources. This study also intends to provide the practical basis data in order to establish specific alternatives for GHG mitigation in residential sector with examining the cause analysis affecting $CO_2$ emission increases from 1995 to 2007. The results of this study show a 6.6% increase in the total $CO_2$ from 60,636 thousand tons in 1995 to 64,611 thousand tons in 2007 by using energy in residential sector. Heating is the greatest $CO_2$ emission sector by use, followed electric appliances, cooking, lighting and cooling. Heating sector shows 56.6% reductions from 71.5% in 1995 and as do cooling and electric home appliances, with a 2.4% increase from 0.6% and a 21.8% increase from 14.2% respectively. To analyze factors resulted in $CO_2$ emissions in residential sector, the relevant indicator change rate from 2005 to 2007 was examined. The results find that population, the number of household, housing areas, family patterns, and family income resulted in the $CO_2$ emissions increase in residential sector from 1995 to 2007. On the other hand, carbon intensity and energy intensity contribute to $CO_2$ reduction in residential sector with -2% and -38.7% respectively because of the energy conversion and the improvement of energy efficiency in electronic appliances. This study can be used as a reference when taken account of the reality and considered the introduction of highly effective measures to increase the possibility of mitigation potential in residential sector hereafter.

• Journal of the Korean Society of Radiology
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• v.13 no.4
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• pp.613-621
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• 2019

The purpose of this study is to evaluate the effectiveness of supportive devices which are for minimizing the patient's movement during lower extremity angiography and to verify image quality of phantom by analyzing of Mask image, DSA image and Roadmap image into SNR and CNR. As a result of comparing SNR with CNR of mask image obtained by DSA technique using the phantom alone and phantom placed on the supportive devices, there was no significant difference between about 0~0.06 for SNR and about 0~0.003 for CNR. The study showed about 0.11~0.35 for SNR and 0.016~0.031 for CNR of DSA imaging by DSA technique about only water phantom of the blood vessel model and the water phantom placed on the device. Analyzing SNR and CNR of Roadmap technique about water phantom on the auxiliary device (hardboard paper, pomax, polycarbonate, acrylic) and water phantom alone, there was no significant difference between 0.02~0.05 for SNR and 0.002~0.004 for CNR. In conclusion, there was no significant difference on image quality by using supportive devices made by hardboard paper, pomax, polycarbonate or acryl regardless of whether using supportive devices or not. Supportive devices to minimize of the patient's movement may reduce the total amount of contrast, exam-time, radiation exposure and eliminate risk factors during angiogram. Supportive devices made by hardboard paper can be applied easily during angiogram due to advantages of reasonable price and simple processing. It is considered that will be useful to consider cost efficiency and types of materials and their properties in accordance with purpose and method of the study when the operator makes and uses supportive devices.

• Journal of Korean Society of Forest Science
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• v.108 no.1
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• pp.29-39
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• 2019

The objective of this study was to suggest a suitable amount of fertilizer using the changes in growth performances and soil properties for improving survival and quality of Zelkova serrata trees in a harvested Pinus rigida plantation. One-year-old containerized seedlings of Z. serrata were planted with the density of 3000 seedlings $ha^{-1}$ in end of March 2011 at Gwangneung experimental forest, Pocheon. Solid compound fertilizer (N:P:K=3:4:1) were applied yearly in three amounts (control: no fertilization, F1: $180kg\;ha^{-1}$, and F2: $360kg\;ha^{-1}$) every May from 2011 to 2013. We analyzed soil properties before (2011) and after (2012 and 2017) fertilization. And we measured the root collar diameter and height of Z. serrata trees from 2011 to 2016, and then calculated H/D ratio and stem volume. Soil properties at Z. serrata plantation did not show difference according to fertilization level in every investigation year. As time passed after planting, however, concentrations of total nitrogen and available phosphorus were increased from decreased. The growth of root collar diameter, height and stem volume of Z. serrata trees at F2 plot were significantly higher those at the other plots after only 2 years of fertilization. Because Z. serrata tree demand to more nutrient during the early growing period. The survival rate of Z. serrata trees at control plot was significantly lower than that at the other plots. This might be due to Z. serrata trees at control plot had not the upper hand from competition with vegetation at the early in planting. However, the growth of height and stem volume of Z. serrata trees between F1 and F2 plots did not show difference over 6 years after planting. Consequently, we could suggest that Z. serrata trees need to F1 fertilization level for considering improving survival and quality of Z. serrata trees and economical efficiency of plantation managements after harvesting P. rigida plantation.

• Journal of agriculture & life science
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• v.51 no.2
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• pp.47-59
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• 2017

The objectives of this study were to select the seeds of Cucurbitaceae and Solanaceae genotypes in terms of superior with bioactive compounds content and to inform sophisticated data for developing the high value-added products. We evaluated to aspects of the antioxidant activity, polyphenol content, and flavonoid contents in seeds from two vegetable family. We used in the Cucurbitaceae(watermelon, squash, bitter gourd, and sponge gourd) and Solanaceae(hot pepper, sweet pepper, and egg plant) the total 408 genotypes. In Cucurbitaceae, polyphenol content of watermelon and squash genotypes were ranged 19.9-343.8 and $6.1-81.2mg{\cdot}100g^{-1}\;DW$, respectively. The polyphenol content of watermelon genotypes was 12% among all genotypes over $160mg{\cdot}100g^{-1}\;DW$. The mean of flavonoid content in watermelon and squash genotypes represented 80 and $41.3mg{\cdot}100g^{-1}\;DW$, respectively. In Solanaceae, flavonoid content of hot pepper genotypes was ranged $64.4-472.5mg{\cdot}100g^{-1}\;DW$, with an average of $165.0mg{\cdot}100g^{-1}$. The 23 hot pepper genotypes were classified over 90% antioxidant activity. The antioxidant activity of sweet pepper was ranged 35.9-90.3%, and 23% of all genotypes represented 82% antioxidant activity. The polyphenol and flavonoid content of egg plant was ranged $38.1-642.0mg{\cdot}100g^{-1}\;DW$ and $14.2-1217.0mg{\cdot}100g^{-1}\;DW$, respectively. In addition, we selected that 8 egg plant with the superior genotypes for antioxidant activity, polyphenol, and flavonoid content. Results revealed that there was significant variation of antioxidant activity and bioactive compounds contents in both vegetable famaily. In addition, we suggested that selected genotypes seeds with high contain bioactive compounds will be more efficiency to develop natural value-added products.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.1
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• pp.62-70
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• 2021

The purpose of this study was to determine the optimal digestible energy levels on pregnancy mares. Physical changes and fecal microorganism in pregnant horse and changes in birth characteristics of neonatal foals were investigated. The experiment was conducted by 18 mares (Jeju corssed bred, older than 36 months) into three treatment groups. The experimental diet consisted of 80%, 100%, 120% digestible energy levels based on NRC. The average daily intake was lower in the 120% (8.75±1.01) than the 100% (9.34±0.92), 80% (9.14±0.88) and there was significant difference (p<0.05). The feed efficiency was lower in the 120% than 80%, 100% (p<0.05). Total cholesterol, HDL-cholesterol, LDL-cholesterol and triglyceride was higher in 120% than others (p<0.05). However there were no health problem and there was no difference between the treatment groups in the birth characteristics of neonatal foals. At the phylum level, Fibrobactres was difference by digestible energy levels, 80% (8.53%) was higher than 100%, 120%. At the genus level, Bacteroides and Kineothrix increased in fecal proportions with increasing digestible energy levels (p<0.05). Fibrobacter showed higher composition at 80% than 100% and 120% (p<0.05).

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1669-1679
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• 2020

This study examines the washing effect of precipitation on particulate matter (PM) and the rainwater quality (pH, electrical conductivity (EC), water-soluble ions concentration). Of six rain events in total, rainwater samples were continuously collected every 50 mL from the beginning of the precipitation using rainwater collecting devices at Pukyong National University, Busan, South Korea, from March 2020 to July 2020. The collected rainwater samples were analyzed for pH, EC, and water-soluble ions (cations: Na+, Mg2+, K+, Ca2+, NH4+, and anions: Cl-, NO3-, SO42-). The concentrations of particulate matter were continuously measured during precipitation events with a custom-built PM sensor node. For initial rainwater samples, the average pH and EC were approximately 4.3 and 81.9 μS/cm, and the major ionic components consisted of NO3- (5.4 mg/L), Ca2+ (4.2 mg/L), Cl- (4.1 mg/L). In all rainfall events, rainwater pH gradually increased with rainfall duration, whereas EC gradually decreased due to the washing effect. When the rainfall intensities were relatively weak (<5 mm/h), PM10 reduction efficiencies were less than 40%. When the rainfall intensities were enhanced to more than 7.5 mm/h, the reduction efficiencies reached more than 60%. For heavy rainfall events, the acidity and EC, as well as ions concentrations of initial rainwater samples, were higher than those in later samples. This appears to be related to the washing effect of precipitation on PM10 in the atmosphere.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.6
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• pp.727-736
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• 2021

Road tunnel lengths are increasing. Some 1,300 tunnels with 1,102 km in length had been increased till 2019 from 2010. There are 64 tunnels over 3,000 m in length, with their total length adding up to 276.7 km. Safety facilities in the event of a tunnel fire are critical so as to prevent large-scale casualties. Standards for installing disaster prevention facilities are being proposed based on the guidelines of the Ministry of Land, Infrastructure and Transport, but they may be limited to deep underground tunnels. This study was undertaken to provide guidelines for the spacing of evacuation connection passages and the widths of evacuation connection doors. Evacuation with various spacing and widths was simulated in regards to evacuation time, which is the measure of safety, using the evacuation analysis simulation software EXODUS Ver.6.3 and the fire/smoke analysis software SMARTFIRE Ver.4.1. Evacuation connection gates with widths of 0.9 m and 1.2 m, and spacings of 150 m to 250 m, were set to every 20 m. In addition, longitudinal slopes of 6 % and 0 % were considered. It was determined to be safe when the evacuation completion time was shorter than the delay diffusion time. According to the simulation results, all occupants could complete evacuation before smoke spread regardless of the width of the evacuation connection door when the longitudinal slope was 6 % and the interval of evacuation connection passage was 150 m. When the evacuation connection passage spacing was 200 m and the evacuation connection gate width was 1.2 m, all occupants could evacuate when the longitudinal slope was 0 %. Due to difference in evacuation speed according to the longitudinal slope, the evacuation time with a 6 % slope was 114 seconds shorter (with the 190 m connection passage) than with a 0 % slope. A shorter spacing of evacuation connection passages may reduce the evacuation time, but this is difficult to implement in practice because of economic and structural limitations. If the width of the evacuation junction is 1.2 m, occupants could evacuate faster than with a 0.9 m width. When the width of a connection door is 1.2 m with appropriate connection passage spacing, it might provide a means to increase economic efficiency and resolve structural limitations while securing evacuation safety.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.723-736
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• 2022

In this study, monthly precipitation forecasting models that can predict up to 12 months in advance were constructed for the Geum River basin, and two statistical techniques, multiple linear regression (MLR) and artificial neural network (ANN), were applied to the model construction. As predictor candidates, a total of 47 climate indices were used, including 39 global climate patterns provided by the National Oceanic and Atmospheric Administration (NOAA) and 8 meteorological factors for the basin. Forecast models were constructed by using climate indices with high correlation by analyzing the teleconnection between the monthly precipitation and each climate index for the past 40 years based on the forecast month. In the goodness-of-fit test results for the average value of forecasts of each month for 1991 to 2021, the MLR models showed -3.3 to -0.1% for the percent bias (PBIAS), 0.45 to 0.50 for the Nash-Sutcliffe efficiency (NSE), and 0.69 to 0.70 for the Pearson correlation coefficient (r), whereas, the ANN models showed PBIAS -5.0~+0.5%, NSE 0.35~0.47, and r 0.64~0.70. The mean values predicted by the MLR models were found to be closer to the observation than the ANN models. The probability of including observations within the forecast range for each month was 57.5 to 83.6% (average 72.9%) for the MLR models, and 71.5 to 88.7% (average 81.1%) for the ANN models, indicating that the ANN models showed better results. The tercile probability by month was 25.9 to 41.9% (average 34.6%) for the MLR models, and 30.3 to 39.1% (average 34.7%) for the ANN models. Both models showed long-term predictability of monthly precipitation with an average of 33.3% or more in tercile probability. In conclusion, the difference in predictability between the two models was found to be relatively small. However, when judging from the hit rate for the prediction range or the tercile probability, the monthly deviation for predictability was found to be relatively small for the ANN models.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.41-59
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• 2022

The timely procurement of military supplies is essential to maintain the military's operational capabilities, and contract work is the first step toward timely procurement. In addition, rapid signing of a contract enables consumers to set a leisurely delivery date and increases the possibility of budget execution, so it is essential to improve the contract process to prevent early execution of the budget and transfer or disuse. Recently, research using big data has been actively conducted in various fields, and process analysis using big data and process mining, an improvement technique, are also widely used in the private sector. However, the analysis of contract work in the military is limited to the level of individual analysis such as identifying the cause of each problem case of budget transfer and disuse contracts using the experience and fragmentary information of the person in charge. In order to improve the contract process, this study analyzed using the process mining technique with data on a total of 560 contract tasks directly contracted by the Department of Finance of the Air Force Logistics Command for about one year from November 2019. Process maps were derived by synthesizing distributed data, and process flow, execution time analysis, bottleneck analysis, and additional detailed analysis were conducted. As a result of the analysis, it was found that review/modification occurred repeatedly after request in a number of contracts. Repeated reviews/modifications have a significant impact on the delay in the number of days to complete the cost calculation, which has also been clearly revealed through bottleneck visualization. Review/modification occurs in more than 60% of the top 5 departments with many contract requests, and it usually occurs in the first half of the year when requests are concentrated, which means that a thorough review is required before requesting contracts from the required departments. In addition, the contract work of the Department of Finance was carried out in accordance with the procedures according to laws and regulations, but it was found that it was necessary to adjust the order of some tasks. This study is the first case of using process mining for the analysis of contract work in the military. Based on this, if further research is conducted to apply process mining to various tasks in the military, it is expected that the efficiency of various tasks can be derived.