• Microbiology and Biotechnology Letters
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• v.39 no.1
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• pp.93-96
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• 2011

It has been shown that a nucleotide substitution at position 770 in Escherichia coli 16S rRNA, which is implicated in forming the evolutionary conserved B2c intersubunit bridge, has a detrimental effect on ribosome function. In order to isolate second-site revertants that complement ribosomes containing C770G, we performed a random mutagenesis of the 16S rRNA gene and selected clones that could produce more CAT protein translated by specialized ribosome. One of the clones contained two nucleotide substitutions at positions 569 and 904 (C569G and U904C) and these mutations partially complemented the loss of protein-synthesis ability caused by C770G. Further studies using the isolated revertant will provide information about which part of 16S rRNA is interacting with C770 and the consequence of the structure formed by these interactions in the process of protein synthesis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.3 no.2 s.5
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• pp.129-140
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• 2004

In this paper, we conduct the research about optimal aggregation interval of travel time data on interrupted traffic flow and verify the reliability of AVI collected data by using car plate matching method in RTMS for systematic collection and analysis of link travel time data on interrupted traffic flow rural arterial. We perform Kolmosorov-Smirnov test on AVT collected sample data and on entire population data, and conclude that the sample data does not represent pure random sampling and hence includes sample collection error. We suggest that additional review is necessary to investigate the effectiveness of AVI collected sample data as link representative data. We also develop statistical model by applying two estimation techniques namely point estimation and interval estimation for calculating optimal aggregation interval. We have implemented our model and determine that point estimate is preferable over interval estimate for exactly selecting and deciding optimal aggregation interval. Our final conclusion is that 5-minute aggregation interval is optimal to estimate travel time in RTMS, as is currently being used our investigation is based on AVI data collected from Yang-ji to Yong-in $42^{nd}$ National road.

• Journal of Korean Society of Environmental Engineers
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• v.31 no.9
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• pp.825-830
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• 2009

Pharmaceutical compounds enter the water environment through the diverse pathways. Because their concentration in the water environment was frequently detected in the level of ppt to ppb, the monitoring system should be optimized as much as possible for finding appropriate management policies and technical solutions. One Factor At a Time (OFAT) approach approximating the response with a single variable has been preferred for the optimization of LC-MS/MS operational conditions. However, it is common that variables in analytical instruments are interdependent. Therefore, the best condition could be found by using the statistical optimization method changing multiple variables at a time. In this research, response surface analysis (RSA) was applied to the LC-MS/MS analysis of emerging antibiotic compound, sulfamethoxazole, for the best sensitivity. In the screening test, fragmentation energy and collision voltage were selected as independent variables. They were changed simultaneously for the statistical optimization and a polynomial equation was fit to the data set. The correlation coefficient, $R^2$ valuerepresented 0.9947 and the error between the predicted and observed value showed only 3.41% at the random condition, fragmentation energy of 60 and collision voltage of 17 eV. Therefore, it was concluded that the model derived by RSA successfully predict the response. The optimal conditions identified by the model were fragmentation energy of 116.6 and collision voltage of 10.9 eV. This RSA can be extensively utilized for optimizing conditions of solid-phase extraction and liquid chromatography.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1179-1194
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• 2020

This study investigates the feasibility of three algorithms, K-Nearest Neighbors (K-NN), Random Forest (RF) and Neural Network (NN), for estimating the air temperature of an unobserved area where the weather station is not installed. The satellite image were obtained from Landsat-8 and MODIS Aqua/Terra acquired in 2019, and the meteorological ground weather data were from AWS/ASOS data of Korea Meteorological Administration and Korea Forest Service. In addition, in order to improve the estimation accuracy, a digital surface model, solar radiation, aspect and slope were used. The accuracy assessment of machine learning methods was performed by calculating the statistics of R² (determination coefficient) and Root Mean Square Error (RMSE) through 10-fold cross-validation and the estimated values were compared for each target area. As a result, the neural network algorithm showed the most stable result among the three algorithms with R² = 0.805 and RMSE = 0.508. The neural network algorithm was applied to each data set on Landsat imagery scene. It was possible to generate an mean air temperature map from June to September 2019 and confirmed that detailed air temperature information could be estimated. The result is expected to be utilized for national disaster safety management such as heat wave response policies and heat island mitigation research.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.150-162
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• 2016

This study empirically analyze the effect of government R&D investment to find out whether it complements or substitutes for the firm R&D. In order to do it panel data set was constructed for the period of three years from 2012 to 2014 based on the number of 1301 data by utilizing national technology information service(NTIS) and publicly announced financial statement. Analysis was implemented in consideration of size of the firm(large corporation, small and medium sized firm) of which sample was obtained from only listed company. The result of two-way fixed effect model and two-way random effect model is as follows. In case of large corporation, government R&D investment has an effect of substitute for the company's R&D on the other hand, small and medium sized firm shows an complementary effect. It verifies that current R&D policy is appropriate. Therefore government's direct subsidy is expected to be successful to fertilize firm's innovation by allocating government R&D budget efficiently.

• Journal of Korean Ophthalmic Optics Society
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• v.13 no.1
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• pp.95-99
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• 2008

Purpose: Even refractive error is perfectly corrected by glasses power, the glasses wearer can feel imbalance and uncomfortable by prism effects. The purpose of this study was to investigate subjective imbalance to vertical yoked prism in visually normal subjects. Methods: Visually normal 37 subjects (aged 20 to 31 y) were fully corrected by soft contact lens and worn vertical yoked prism, base up and base down 1, 2, 4, 6, 8 prism diopter(pd) at random order. A rating scale questionnaire was administered to assess quantitatively subjective imbalance to the yoked prism. The near phoria tests were done using Howell-Kim phoria card at 40 cm distance. Results: For the subjective response of imbalance, base up yoked prism was higher than base down yoked prism (t-test: t=4.67, p=0.00) in over 2 prism diopters. The frequency of subjects who feel imbalance by base up vertical yoked prism is higher for near esophoric group than for exophoric group. Conclusions: To reduce subjective imbalance caused by glasses such as dizzy, it needs to make the minimum prism effect, and base down yoked prism is more effective than base up yoked prism in prism effects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.6
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• pp.2038-2045
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• 2010

Households' monthly average income is composed of various factors. This study paper studies focuses on estimating the determinants of a households' monthly average income. The region for analysis consist of three groups, that is, the whole country, a metropolitan city(such as Busan, Daegu, Incheon, Gwangiu, Daejeon, Ulsan.) and Seoul. Analyzing period be formed over a 57 time points(2005. 01~2009. 09). In this paper the dependent variable setting up the households' monthly average income, explanatory (independent) variables are composed of the consumer price index, employment to population ratio, Index of housing sale price, the preceding composite index, loans of housing mortgage, spending rate for care medical expense and the composite stock price index. In looking at the factors which determine the monthly average income, evidence was produced supporting the hypothesis that there is a significant positive relationship between the composite index and housing loans. The study also produced evidence supporting the view that there is a significant negative relationship between employment ratios, the house sale pricing index and spending rates for care or medical needs. The study found that the consumer price index and composite stock price index were not significant variables. The implications of these findings are discussed for further research.

• Journal of Korean Society of Forest Science
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• v.101 no.2
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• pp.213-219
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• 2012

The $5^{th}$ national forest inventory (NFI5) has been reorganized to annual inventory system for providing multi-resources forest statistics at a point in time. The objective of this study is to evaluate statistical estimators for estimating forest growing stock in Chungcheongbuk-Do from annual inventory data. When comparing two estimators; simple random sampling (SRS) and double sampling for post-stratification (DSS), for estimating mean forest growing stock ($m^3/ha$) at each surveyed year, the estimate for DSS in which a population of interest is stratified into three sub-population (forest cover types) was more precise than that for SRS. To combine annual inventory field data, three estimators (Temporally Indifferent Method; TIM, Moving Average; MA, and Weighted Moving Average; WMA) were compared. Even though the estimated mean for TIM and WMA is identical, WMA-DSS is preferred to provide more smaller variance of estimated mean and to adjust for catastrophic events at a surveyed year (so-called "lag bias") by annual inventory data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.81-99
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• 2020

Origin-destination data have been collected and utilized for demand analysis and service design in various fields such as public transportation and traffic operation. As the utilization of big data becomes important, there are increasing needs to store raw origin-destination data for big data analysis. However, it is not practical to store and analyze the raw data for a long period of time since the size of the data increases by the power of the number of the collection points. To overcome this storage limitation and long-period pattern analysis, this study proposes a methodology for compression and origin-destination data analysis with the compressed data. The proposed methodology is applied to public transit data of Sejong and Seoul. We first measure the reconstruction error and the data size for each truncated matrix. Then, to determine a range of principal components for removing random data, we measure the level of the regularity based on covariance coefficients of the demand data reconstructed with each range of principal components. Based on the distribution of the covariance coefficients, we found the range of principal components that covers the regular demand. The ranges are determined as 1~60 and 1~80 for Sejong and Seoul respectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.55-66
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• 2020

This study developed four algorithms and their associated indices that can quantify and qualify road hazards along roadways. Initially, relevant raw data can be collected from commercial vehicles by camera and DTG. Well-processed data, such as potholes, road freezing, and fog, can be generated from the Integrated management system. Road hazard algorithms combine these data with road inventory data in the Data Sharing Platform. Depending on well-processed data, four different road hazard algorithms and their associated indices were developed. To test the algorithms, an experimental plan based on passive DTG attached in probe vehicles was performed at two different test locations. Selection of the test routes was based on historical data. Although there were limitations using random data for commercial vehicles, hazardous roadways sections, such as fog, road freezing, and potholes, were generated based on actual historical data. As a result, no algorithm error was found in the entire test. Because this study provides road hazard information according to a section, not a point, it can be practically helpful to road users as well as road agencies.