• Clean Technology
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• v.27 no.4
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• pp.350-358
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• 2021

The results of this study shows that the combustor temperature ranged from 848.27 to 1,026.80 ℃, averaging about 976.61 ℃, and the NOx concentration increased as the temperature increased. The urea usage ranged from 291.00 to 693.00 kg d^-1, averaging about 542.34 kg d^-1, and the NOx concentration decreased as the urea usage increased. Residence time was about 3.38 to 9.17 s, averaging about 5.22 s, about 2.61 times larger than the 2 s of the design details. This is 1,086 kg h^-1, averaging about 55.71%, compared to the 1,950 kg h^-1 SRF input permission standard. The combustion chamber area is constant, but the residence time is shown to increase with the decrease of exhaust gas. The O₂/CO ratio was 847.05 to 14,877.34, averaging about 3,111.30, and the NOx concentration slightly increased as the O₂/CO ratio increased. As the combustor temperature and O₂/CO ratio increased, the combustion reaction with nitrogen in the air increased and the NOx concentration slightly increased. As the urea usage and residence time increased, the NOx concentration decreased slightly with an increase in reactivity with NOx. The NOx concentration at the stack ranged from 7.88 to 34.02 ppm with an average of 19.92 ppm, and was discharged within the 60 ppm emission limit value. The NOhx emission factor was 1.058 to 1.795 kg ton^-1, averaging about 1.450 kg ton^-1. This value was about 24.87% of the maximum emission factor of 5.830 kg ton^-1 of other solid fuels. Other synthetic resins and industrial wastes were 79.80% and 43.65% compared to 1.817 kg ton^-1 and 3.322 kg ton^-1, respectively. This value was similar to 1.400 kg ton^-1 of RDF in the NIER notice (2005-9), 10.98% compared to the maximum SRF of 13.210 kg ton^-1. Therefore, the NOx emission factor had a large deviation.

• Journal of Climate Change Research
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• v.3 no.1
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• pp.71-88
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• 2012

The global warming is probably the most significant issue of concern all over the world and according to the report published by the Intergovernmental Panel on Climate Change (IPCC), the average temperature and extent of global warming around the globe have been on the rise and so have the uncertainty for the future. Such effects of global warming have adverse effects on basic foundation of the mankind in numerous ways and water resource is no exception. The researches on water resources assessment for climate change are significant enough to be used as the preliminary data for researches in other fields. In this research, a total of 124 peer-reviewed publications and 57 reports on the subject of research on climate change related to water resources, that has been carried out so far in Korea has been reviewed. The research on climate change in Korea (inclusive of the peer-reviewed articles and reports) has mainly focused on the future projection and assessment. In the fields of hydrometeorology tendency and projection, the analysis has been carried out with focus on surface water, flood, etc. for hydrological variables and precipitation, temperature, etc. for meteorological variables. This can be attributed to the large, seasonal deviation in the amount of rainfall and the difficulty of water resources management, which is why, the analysis and research have been carried out with focus on those variables such as precipitation, temperature, surface water, flood, etc. which are directly related to water resources. The future projection of water resources in Korea may differ from region to region; however, variables such as precipitation, temperature, surface water, etc. have shown a tendency for increase; especially, it has been shown that whereas the number of casualties due to flood or drought decreases, property damage has been shown to increase. Despite the fact that the intensity of rainfall, temperature, and discharge amount are anticipated to rise, appropriate measures to address such vulnerabilities in water resources or management of drainage area of future water resources have not been implemented as yet. Moreover, it has been found that the research results on climate change that have been carried out by different bodies in Korea diverge significantly, which goes to show that many inherent uncertainties exist in the various stage of researches. Regarding the strategy in response to climate change, the voluntary response by an individual or a corporate entity has been found to be inadequate owing to the low level of awareness by the citizens and the weak social infrastructure for responding to climate change. Further, legal or systematic measures such as the governmental campaign on the awareness of climate change or the policy to offer incentives for voluntary reduction of greenhouse gas emissions have been found to be insufficient. Lastly, there has been no case of any research whatsoever on the anticipated effects on the economy brought about by climate change, however, there are a few cases of on-going researches. In order to establish the strategy to prepare for and respond to the anticipated lack of water resources resulting from climate change, there is no doubt that a standardized analysis on the effects on the economy should be carried out first and foremost.

• Journal of Environmental Impact Assessment
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• v.28 no.3
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• pp.183-200
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• 2019

In this study, the characteristics of seasonal $PM_{2.5}$ behavior in South Korea and other Northeast Asian regions were analyzed by using the $PM_{2.5}$ ground measurement data, weather data, WRF and CMAQ models. Analysis of seasonal $PM_{2.5}$ behavior in Northeast Asia showed that $PM_{2.5}$ concentration at 6 IMS sites in South Korea was increased by long-distance transport and atmospheric congestion, or decreased by clean air inflow due to seasonal weather characteristics. As a result of analysis by applying BFM to air quality model, the contribution from foreign countries dominantly influenced the $PM_{2.5}$ concentrations of Baengnyeongdo due to the low self-emission and geographical location. In the case of urban areas with high self-emissions such as Seoul and Ulsan, the $PM_{2.5}$ contribution from overseas was relatively low compared to other regions, but the standard deviation of the season was relatively high. This study is expected to improve the understanding of the air pollutant phenomenon by analyzing the characteristics of $PM_{2.5}$ behavior in Northeast Asia according to the seasonal weather condition change. At the same time, this study can be used to establish the air quality policy in the future, knowing that the contribution of $PM_{2.5}$ concentration to the domestic and overseas can be different depending on the regional emission characteristics.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.217-225
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• 2019

The purpose of this study was to quantitate signal to noise ratio and contrast to noise ratio of the portal vein using CT and 3.0T MRI and to investigate the optimal imaging device. Twenty patients who inspective CT and 3.0T MRI between February 2018 and April 2018 were randomly assigned to receive data from the picture archiving communication system. The SNR and CNR values were evaluated by measuring the mean and standard deviation of the region of interest of the four regions of the portal vein (the main portal vein, the right vein, the left vein, and the middle vein). The results showed that SNR was 9.180.72 in the right context, 9.410.84 in the left context, 9.540.59 in the middle context, 9.550.75 in the order context, and 22.292.03 in the right context and 25.893 in the 3.0T MRI. 19, median context: 24.392.87, and order Mac: 26.642.30 (p<0.05). CNR was 3.790.68 in the CT context, 3.740.65 in the left context, 3.710.39 in the middle context, 3.790.68 in the order context, 9.490.65 in the right context, and 11.0001.90 in the 3.0T MRI, Intermediate context: 12.701.75, order Mac: 10.010.98, 3.0T MRI was higher than CT (p<0.05). In conclusion, SNR and CNR values were higher in the 3.0T MRI than CT in the 4 portal regions. Therefore, 3.0T MRI using non-ionizing radiation was the most superior imaging equipment than CT.

• (The) Korean Journal of Educational Psychology
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• v.23 no.3
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• pp.645-663
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• 2009

The purpose of this study is to develop and verify a Korean Diagnostic Scale of Multiple Intelligence(MI), which will be an alternative test to avoid problems with former Shearer's MI test and to adopt H. Gardner's suggestions to develop MI assessment. The test is developed 5 types; kindergartner, elementary lower grader, elementary upper grader, middle schooler, high schooler test. A form of test is diversified with 3 types; multiple-choice items for accomplishment, true or false items for ability, and self-reported items with likert scale for interest and ability. According to H. Gardner's suggestions, we have tried to reanalyze key component of MI, analyze an overlapping or hierarchical relationship between intelligences, develop intelligences-fair items, diversify form of item. We have developed a final standardized test through a primary, secondary preliminary-test analysis, and sampled 5,585 students by age, gender, and regional groups. As a result of this sampling test, we can get a norm score and compare individuals with other's score relatively. To verify this test, we analyzed behavior observation, mean, standard deviation, a percentage of correct answers, reliability of each test type, correlation between intelligence scales, Kruskal-Wallis test of mean rank of career choice by intelligences. As a result of correlation analysis between sub-intelligence scales, we can conclude that this MI test is satisfied with intelligence independent assumption. Besides, as non-parametric statistics test(Kruskal-Wallis) of career choice by intelligences, we can identify that MI is related with domain of career choice. This test is not a linguistic and logical-mathematical biased test but a intelligences-fair test. It makes us compare individual's potential with a norm score. Besides, it could be useful as a means of educational prescription or counsel in comparison with ability, interest, and accomplishment of individual. But this test is limited to do factor or correlation analysis between types of sub-test, because items are minimized for a time-constraint and a heavy burden of test receiver. But if it could be tested with increased items by two sessions, further research could be expected to get over this constraints and do a further validation analysis.

• Journal of Food Hygiene and Safety
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• v.34 no.2
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• pp.148-157
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• 2019

An optimized analytical method for sodium iron chloriphyllin in foods was established and verified by using high performance liquid chromatography with attached diode array detection. An Inertsil ODS-2 column and methanol-water (80:20 containing 1% acetate) as a mobile phase were employed. The limit of detection and quantitation of sodium iron chloriphyllin were 0.1 and 0.3 mg/kg, respectively, and the linearity of calibration curve was excellent ($R^2=0.9999$). The accuracy and precision were 93.9~104.95% and 2.0~7.7% in both inter-day and intra-day tests. Recoveries for candy and salad dressing were ranged between 93 and 104% (relative standard deviation, (RSD) 0.3~4.3%), and between 83 and 115% (RSD 1.2~2.0%), respectively. Liquid chromatography mass spectrometry was used to verify the main components of sodium iron chlorophyllin which were Fe-isochlorin e4 and Fe-chlorin e4.

• 한국노년학
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• v.38 no.3
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• pp.745-766
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• 2018

The purpose of this study is to examine the research trends regarding the published articles in the Journal of Korean Gerongological Society within the past 10 years. This study is based on the article written by Won and Mo (2008). This article classified previously published studies into themes, methods, and application of theory. Out of the total of 187 articles published in the past 10 years, 11 articles were about social change and institution, 94 articles were about social issues, 12 articles were about social problems and deviation, 42 articles were about social culture, 14 papers were about gerontological theory and 13 papers were about residence/architecture. In the last 10 years, the most popular topic was around the various ways aging. New topic that emerged was the effect of IT and technology on the quality of life among the older adults. Other topics that gained interest were age discrimination and prejudice on aging. Trends in research methods showed increased use of qualitative methods. In the future, more research needs to be completed to theorize the results of quantitative research. Furthermore, the use of qualitative research methods needs to be increased in order to understand the lives of older adults in depth. Through more meta analysis, the results of past research articles should be synthesized to get a bigger picture of the Korean older adults.

• (The) Research of the performance art and culture
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• no.20
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• pp.129-161
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• 2010

Women's social status is marginal in the patriarchal system, therefore it is not easy to express their's desire. Women's social role are restricted by the Confucian culture in the late of Chosun Dinasty. But women freely expressed their's gamseong(感性) by singing the folk songs. Many researches have focused on the reality of life or the structure and meanings of the women's folk songs. On the contrary, no one has paid attention to the gamseong in the women's folk songs. This is the reason why this thesis focused on the aspects of gamseong in the women's folk songs. The aspect of gamseong expression in women's folk songs can be classfied as follow: HAN(恨) resulting from living with one's husband's parents (Si-jip-sa-ri); LONGING caused by parting with the lover; HOPE due to childbirth and bringing up; SHIN-MYOUNG(神明) through deviation and liberation. In conclusion, We can find out women's gamseong would be formed from the their own roles and relationship with the others. Besides they could offset their sorrow and cure their pain through loving others and selfloving.

• Analytical Science and Technology
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• v.31 no.6
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• pp.240-246
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• 2018

The present study analyzed standard samples of three types of aluminum matrix certified reference materials (CRM) using GD-MS. Calibration curves were constructed for 13 elements (Mg, Si, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, Ga, Sn, and Pb), with the slope representing the relative sensitivity factor (RSF). The x- and y-axes of the calibration curve represented ion beam ratio (IBR) and the authenticated value of the standard sample, respectively. In order to evaluate precision and linearity of the calibration curve, RSD and the coefficient of determination were calculated. Curve RSD for every element reflected high precision (within 10 %). For most elements, the coefficient of determination was ${\geq}0.99$, indicating excellent linearity. However, vanadium, nickel, and gallium curves exhibited relatively low linearity (0.90~0.95), likely due to their narrow concentration ranges. Standard RSF was calculated using the slope of the curve generated for three types of CRM. Despite vanadium, nickel, and gallium exhibiting low coefficients of determination, their standard RSF resembled that of the three types of CRM. Therefore, the RSF method may be used for element quantitation. Standard iron matrix samples were analyzed to verify the applicability of the aluminum matrix standard RSF, as well as to calculate the RSD-estimated error of the measured value relative to the actual standard value. Six elements (Al, Si, V, Cr, Mn, and Ni) exhibited an RSD of approximately 30 %, while the RSD of Cu was 77 %. In general, Cu isotopes are subject to interference: $^{63}Cu$ to $^{54}Fe^{2+}-^{36}Ar$ and $^{65}Cu$ to $^{56}Fe-Al^{3+}$ interference. Thus, the influence of these impurities may have contributed to the high RSD value observed for Cu. To reliably identify copper, the resolution should be set at ${\geq}8000$. However, high resolutions are inappropriate for analyzing trace elements, as it lowers ion permeability. In conclusion, quantitation of even relatively low amounts of six elements (Al, Si, V, Cr, Mn, and Ni) is possible using this method.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.239-251
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• 2019

Statistical methods such as moving averages, Kalman filtering, exponential smoothing, regression analysis, and ARIMA (autoregressive integrated moving average) have been used for stock market predictions. However, these statistical methods have not produced superior performances. In recent years, machine learning techniques have been widely used in stock market predictions, including artificial neural network, SVM, and genetic algorithm. In particular, a case-based reasoning method, known as k-nearest neighbor is also widely used for stock price prediction. Case based reasoning retrieves several similar cases from previous cases when a new problem occurs, and combines the class labels of similar cases to create a classification for the new problem. However, case based reasoning has some problems. First, case based reasoning has a tendency to search for a fixed number of neighbors in the observation space and always selects the same number of neighbors rather than the best similar neighbors for the target case. So, case based reasoning may have to take into account more cases even when there are fewer cases applicable depending on the subject. Second, case based reasoning may select neighbors that are far away from the target case. Thus, case based reasoning does not guarantee an optimal pseudo-neighborhood for various target cases, and the predictability can be degraded due to a deviation from the desired similar neighbor. This paper examines how the size of learning data affects stock price predictability through k-nearest neighbor and compares the predictability of k-nearest neighbor with the random walk model according to the size of the learning data and the number of neighbors. In this study, Samsung electronics stock prices were predicted by dividing the learning dataset into two types. For the prediction of next day's closing price, we used four variables: opening value, daily high, daily low, and daily close. In the first experiment, data from January 1, 2000 to December 31, 2017 were used for the learning process. In the second experiment, data from January 1, 2015 to December 31, 2017 were used for the learning process. The test data is from January 1, 2018 to August 31, 2018 for both experiments. We compared the performance of k-NN with the random walk model using the two learning dataset. The mean absolute percentage error (MAPE) was 1.3497 for the random walk model and 1.3570 for the k-NN for the first experiment when the learning data was small. However, the mean absolute percentage error (MAPE) for the random walk model was 1.3497 and the k-NN was 1.2928 for the second experiment when the learning data was large. These results show that the prediction power when more learning data are used is higher than when less learning data are used. Also, this paper shows that k-NN generally produces a better predictive power than random walk model for larger learning datasets and does not when the learning dataset is relatively small. Future studies need to consider macroeconomic variables related to stock price forecasting including opening price, low price, high price, and closing price. Also, to produce better results, it is recommended that the k-nearest neighbor needs to find nearest neighbors using the second step filtering method considering fundamental economic variables as well as a sufficient amount of learning data.