• Journal of Food Hygiene and Safety
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• v.19 no.1
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• pp.12-18
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• 2004

Ofloxacin, norfloxacin, ciprofloxacin, and enrofloxacin in chicken muscle were seperated by liquid extraction and determined with high performance liquid chromatography (HPLC) with fluorescence detector. Analysis was carried out using following conditions; Cl8 column (250${\times}$4.6 mm i.d. 5 ${\mu}{\textrm}{m}$ particle size), mobile phase composed of D.W. (containing 0.4% triethylamine and phospholic acid): methanol : acetonitrile (800:100:100, v/v/v), isocratic pump at a flow rate of 1.0 $m\ell$/min and 50 ${mu}ell$ of injection volume, fluorescence detector with EX278 nm/EM.456 nm. The calibration curves of four fluoroquinolones showed linearity (${\gamma}$$^2$$\geq$0.999) at concenration range of 0.025-0.6 $\mu\textrm{g}$/ml. The recoveries in fortified chicken muscle represented more than 80% with low coefficient of variation (〈10%) for concentration range of four fluoroquinolones. The detection limits for ofloxacin, norfloxacin, ciprofloxacin, and enrofloxacin were 23.5, 3.4, 3.0 and 2.5 ng/g in chicken muscle, respectively. We also monitored fluoroquinolones residue in muscle of chickens (broiler 1:227, Korean native chicken 219, laying chicken 77) using EEC-4-plate screening and HPLC conformation methods. Ten(broiler 5, Korean native chicken 5) out of the fifteen samples which were positively detected by EEC-plate screening method from 1,523 chicken meat were confirmed with ciprofloxacin and enrofloxacin by HPLC. The ranges of residual concentration were 0-0.12 ppm for ciprofloxacin and 0.01-6.79 ppm for enrofloxacin. In conclusion, our method could be applied effectively to determine four fluoroquinolones residues in chicken meat, and further survey for fluoroquinolones residue in chicken meat are needed for more effective control of fluoroquinolones used in livestock.

• Journal of Food Hygiene and Safety
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• v.29 no.2
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• pp.131-140
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• 2014

The objective of this study was to develop a simultaneous method of 8 penicillin antibiotics including amoxicillin, ampicillin, cloxacillin, dicloxacillin, nafcillin, oxacillin, penicillin G and penicillin V in meat using LC-MS/MS. The procedure involves solid phase extraction with HLB cartridge and subsequent analysis by LC-MS/MS. To optimize MS analytical condition of 8 compounds, each parameter was established by multiple reaction monitoring in positive ion mode. The chromatographic separation was achieved on a $C_{18}$ column with a mobile phase of 0.05% formic acid and 0.05% formic acid in acetonitrile at a flow rate of 0.2 mL/min for 20 min with a gradient elution. The developed method was validated for specificity, linearity, accuracy and precision in beef, pork and chicken. The recoveries were 71.0~106%, and relative standard deviations (RSD) were 4.0~11.2%. The limit of detection (LOD) and the limit of quantification (LOQ) were 0.003~0.008 mg/kg and 0.01~0.03 mg/kg, respectively, that are below maximum residue limit (MRL) of the penicillins. This study also performed survey of residual penicillin antibiotics for 193 samples of beef, pork and chicken collected from 9 cities in Korea. Penicillins were not found in all the samples except a sample of pork which contained cloxacillin (concentration of 0.08 mg/kg) below the MRL (0.3 mg/kg).

• Korean Journal of Environmental Biology
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• v.35 no.4
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• pp.549-556
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• 2017

Rivers continuously transport terrestrial organic carbon matter to the estuary and the ocean, and they play a critical role in productivity and biodiversity in the marine ecosystem as well as the global carbon cycle. The amount of terrestrial organic carbon transporting from the rivers to ocean is an essential piece of information, not only for the marine ecosystem management but also the carbon budget within catchment. However, this phenomenon is still not well understood. Most large rivers in Korea have a well-established national monitoring system of the river flow and the TOC (Total Organic Carbon) concentration from the mountain to the river mouth, which are fundamental for estimating the amount of the TOC flux. We estimated the flux of the total terrestrial organic carbon of five large rivers which flow out to the Yellow Sea, using the data of the national monitoring system (the monthly mean TOC concentration and the monthly runoff of river flow). We quantified the annual TOC flux of the five rivers, showing their results in the following order: the Han River ($18.0{\times}10^9gC\;yr^{-1}$)>>Geum River ($5.9{\times}10^9gC\;yr^{-1}$)>Yeongsan River ($2.6{\times}10^9gC\;yr^{-1}$)>Sumjin River ($2.0{\times}10^9gC\;yr^{-1}$)>>Tamjin River ($0.2{\times}10^9gC\;yr^{-1}$). The amount of the Han River, which is the highest in the Korean rivers, corresponds to be 4% of the annual total TOC flux of in the Yellow River, and moreover, to be 0.6% of Yangtze River.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Journal of Korean Society of Forest Science
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• v.90 no.1
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• pp.43-54
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• 2001

Genetic differentiation of populations is resulted from the environmental and the genetic effects, and the interactions between them. Whereas, the major factors influencing to the genetic differentiation within populations are the gene flow induced by seed or pollen dispersial, the microsite heterogeneity, and the density-dependent distribution of individuals. For the purpose of studying spatial genetic structure and the distribution pattern of Korean pines(Pinus koraiensis), we set up one $100{\times}100m$ plot at a Korean pine stand in Quercus mongolica community on Mt. Jumbong in Korea. To estimate the coefficient of spatial autocorrelation as Moran's index and an analogue, simple block distance, isozyme markers were analyzed in 325 Korean pines. For 11 polymorphic loci observed in 9 enzyme systems, the average percentage of polymorphic loci, the observed and expected heterozygocity were 72.2% 0.200, and 0.251, respectively. It was revealed the excess of homozygotes was observed in the plot, which suggests that here may be more number of consanguineous trees than expected. On the basis of isozyme genotypes observed in this study, 325 trees were classified into 147 groups in which the maximum number of trees for one group was 34. From the distance class of 24-32m, the genetic heterogeneity began to increase. The variation of simple block distance against the growth performance by tree height and diameter also showed the same trend at 24~32m class. According to high fixation index(F=0.204), the spatial genetic structure within a stand, the analysis of the growth performance, and the distribution patterns of identical genotypes, we inferred that the genetic structure of a Korean pine stand in Mt. Jumbong has been maintained rather density-dependent mechanism than the gene flow, such as the pollen dispersial or the heavy input of seeds following the forest gaps. The genetic patchy size was determined between 24~32m, which suggests that the selection of individuals for the ex situ conservation of Korean pine in Mt. Jumbong may be desirable to be made with the spatial distance over 37 meters between trees.

• Korean Journal of Remote Sensing
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• v.26 no.2
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• pp.251-262
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• 2010

In order to provide quantitative control of the standard products of Geostationary Ocean Color Imager (GOCI), on-board radiometric correction, atmospheric correction, and bio-optical algorithm are obtained continuously by comprehensive and consistent calibration and validation procedures. The calibration/validation for radiometric, atmospheric, and bio-optical data of GOCI uses temperature, salinity, ocean optics, fluorescence, and turbidity data sets from buoy and platform systems, and periodic oceanic environmental data. For calibration and validation of GOCI, we compared radiometric data between in-situ measurement and HyperSAS data installed in the Ieodo ocean research station, and between HyperSAS and SeaWiFS radiance. HyperSAS data were slightly different in in-situ radiance and irradiance, but they did not have spectral shift in absorption bands. Although all radiance bands measured between HyperSAS and SeaWiFS had an average 25% error, the 11% absolute error was relatively lower when atmospheric correction bands were omitted. This error is related to the SeaWiFS standard atmospheric correction process. We have to consider and improve this error rate for calibration and validation of GOCI. A reference target site around Dokdo Island was used for studying calibration and validation of GOCI. In-situ ocean- and bio-optical data were collected during August and October, 2009. Reflectance spectra around Dokdo Island showed optical characteristic of Case-1 Water. Absorption spectra of chlorophyll, suspended matter, and dissolved organic matter also showed their spectral characteristics. MODIS Aqua-derived chlorophyll-a concentration was well correlated with in-situ fluorometer value, which installed in Dokdo buoy. As we strive to solv the problems of radiometric, atmospheric, and bio-optical correction, it is important to be able to progress and improve the future quality of calibration and validation of GOCI.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.3
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• pp.375-388
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• 2019

Accurate evaluation of sea-to-air $CO_2$ flux and its variability is crucial information to the understanding of global carbon cycle and the prediction of atmospheric $CO_2$ concentration. $fCO_2$ observations are sparse in space and time in the East Sea. In this study, we derived high resolution time series of surface $fCO_2$ values in the southwest East Sea, by feeding sea surface temperature (SST), salinity (SSS), chlorophyll-a (CHL), and mixed layer depth (MLD) values, from either satellite-observations or numerical model outputs, to three machine learning models. The root mean square error of the best performing model, a Random Forest (RF) model, was $7.1{\mu}atm$. Important parameters in predicting $fCO_2$ in the RF model were SST and SSS along with time information; CHL and MLD were much less important than the other parameters. The net $CO_2$ flux in the southwest East Sea, calculated from the $fCO_2$ predicted by the RF model, was $-0.76{\pm}1.15mol\;m^{-2}yr^{-1}$, close to the lower bound of the previous estimates in the range of $-0.66{\sim}-2.47mol\;m^{-2}yr^{-1}$. The time series of $fCO_2$ predicted by the RF model showed a significant variation even in a short time interval of a week. For accurate evaluation of the $CO_2$ flux in the Ulleung Basin, it is necessary to conduct high resolution in situ observations in spring when $fCO_2$ changes rapidly.

• Journal of Intelligence and Information Systems
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• v.25 no.2
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• pp.99-122
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• 2019

According to the recent IDC (International Data Corporation) report, as from 2025, the total volume of data is estimated to reach ten times higher than that of 2016, corresponding to 163 zettabytes. then the main body of generating information is moving more toward corporations than consumers. So-called "the wave of Big-data" is arriving, and the following aftermath affects entire industries and firms, respectively and collectively. Therefore, effective management of vast amounts of data is more important than ever in terms of the firm. However, there have been no previous studies that measure the effects of big data investment, even though there are number of previous studies that quantitatively the effects of IT investment. Therefore, we quantitatively analyze the Big-data investment effects, which assists firm's investment decision making. This study applied the Event Study Methodology, which is based on the efficient market hypothesis as the theoretical basis, to measure the effect of the big data investment of firms on the response of market investors. In addition, five sub-variables were set to analyze this effect in more depth: the contents are firm size classification, industry classification (finance and ICT), investment completion classification, and vendor existence classification. To measure the impact of Big data investment announcements, Data from 91 announcements from 2010 to 2017 were used as data, and the effect of investment was more empirically observed by observing changes in corporate value immediately after the disclosure. This study collected data on Big Data Investment related to Naver 's' News' category, the largest portal site in Korea. In addition, when selecting the target companies, we extracted the disclosures of listed companies in the KOSPI and KOSDAQ market. During the collection process, the search keywords were searched through the keywords 'Big data construction', 'Big data introduction', 'Big data investment', 'Big data order', and 'Big data development'. The results of the empirically proved analysis are as follows. First, we found that the market value of 91 publicly listed firms, who announced Big-data investment, increased by 0.92%. In particular, we can see that the market value of finance firms, non-ICT firms, small-cap firms are significantly increased. This result can be interpreted as the market investors perceive positively the big data investment of the enterprise, allowing market investors to better understand the company's big data investment. Second, statistical demonstration that the market value of financial firms and non - ICT firms increases after Big data investment announcement is proved statistically. Third, this study measured the effect of big data investment by dividing by company size and classified it into the top 30% and the bottom 30% of company size standard (market capitalization) without measuring the median value. To maximize the difference. The analysis showed that the investment effect of small sample companies was greater, and the difference between the two groups was also clear. Fourth, one of the most significant features of this study is that the Big Data Investment announcements are classified and structured according to vendor status. We have shown that the investment effect of a group with vendor involvement (with or without a vendor) is very large, indicating that market investors are very positive about the involvement of big data specialist vendors. Lastly but not least, it is also interesting that market investors are evaluating investment more positively at the time of the Big data Investment announcement, which is scheduled to be built rather than completed. Applying this to the industry, it would be effective for a company to make a disclosure when it decided to invest in big data in terms of increasing the market value. Our study has an academic implication, as prior research looked for the impact of Big-data investment has been nonexistent. This study also has a practical implication in that it can be a practical reference material for business decision makers considering big data investment.

• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.101-112
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• 2019

Over the last few years, air pollution ($PM_{10}$, $PM_{2.5}$) in the Seoul metropolitan area (SMA) has emerged as one of the most concerned and threatening environmental issues among the residents. It brings about various harmful effects on human health, as well as ecosystem and industrial activities. Governments and individuals pay various costs to mitigate the level of air pollutants. This study aims to empirically find the willingness to pays (WTP) among the parents from different socio-cultural groups - international and domestic groups to mitigate air pollution ($PM_{10}$, $PM_{2.5}$) in their residential area. Contingent Valuation Methods (CVM) is used with employing single-bounded dichotomous choice technique to elicit the respondent's WTP. Using tobit (censored regression) and probit models, the monthly mean WTP of the pooled sample for green electricity which contributes to improve air quality in the region was estimated as 3,993 KRW (3.58 USD). However, the mean WTP between the international group and domestic group through a sub-sample analysis shows broad distinction as 3,325KRW (2.98 USD) and 4,449 KRW (3.98 USD) respectively. This is because that socio-cultural characteristics of each group such as socio-economic status, personal experience, trust in institutions and worldview are differently associated with the WTP. Based on the results, the society needs to raise awareness of lay people to find a strong linkage between the current PM issue and green electricity. Also, it needs to improve trust in the government's pollution abatement policy to mobilize more assertive participation of the people from different socio-cultural background.

• ANNALS OF ANIMAL RESOURCE SCIENCES
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• v.29 no.4
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• pp.150-157
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• 2018

The Zygote arrest 1 (ZAR1) gene is known to affect early embryonic development in various vertebrates. In this study, we performed the association analysis to check whether there is any significant relationship between semen kinematic characteristics and the ZAR1 gene. To determine semen kinematic characteristics, we measured motility (MOT), straight-line velocity (VSL), curvilinear velocity (VCL), average path velocity (VAP), linearity (LIN), straightness (STR), amplitude of lateral head displacement (ALH), and beat cross frequency (BCF) of spermatozoa in boars. In order to detect single nucleotide polymorphisms (SNPs), we extracted genomic DNA from multiple Duroc boars, and then subsequently used them in sequencing reactions. As a result, three SNPs were detected in the intronic region of ZAR1 gene (g.2435T>C in intron 2, g.2605G>A and g.4633A>C in intron 3 ). SNPs g.2435T>C and g.2605G>A were significantly associated with MOT (p<0.01) and VSL (p<0.05), and g.4633A