• Environmental and Resource Economics Review
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• v.13 no.4
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• pp.717-734
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• 2004

This paper examined the statistical goodness-of-fit tests for biological growth model in bioeconomic analysis. Some authors estimated usually growth function for fish in the world. However, few studies have estimated growth equations for the bivalve species. Thus, this paper studied the common functional forms of fitting growth equations for cham scallops considering environmental factors and production styles. The following functional forms are considered: linear, log-reciprocal, double log, polynomial and linear with interactions. Results of fitting these various functional forms with real data are compared and evaluated using standard statistical goodness-of-fit tests. Results also indicate that log-reciprocal function is statistically the best fit to the real data. Therefore, the log-reciprocal function is decided the best function describing cham scallop biological growth and hence might be useful for economic evaluation(i.e., optimal harvesting time).

• Journal of Pharmaceutical Investigation
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• v.41 no.5
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• pp.309-315
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• 2011

A sensitive and specific liquid chromatographic method coupled with tandem mass spectrometry (LC-MS/MS) was developed for the analysis of ambroxol (active moiety of acebrophylline). After acetonitrile precipitation of proteins from plasma samples, ambroxol and the domperidone (internal standard, IS) were eluted on a C18 column. The isocratic mobile phase was consisted of 10 mM ammonium acetate and methanol (10 : 90, v/v), with flow rate at 0.2 mL/min. A tandem mass spectrometer, as detector, was used for quantitative analysis in positive mode by a multiple reaction monitoring mode to monitor the m/z 379.2${\rightarrow}$264.0 and the m/z 426.2${\rightarrow}$175.1 transitions for ambroxol and the IS, respectively. Twenty four healthy Korean male subjects received two capsules (100 mg ${\times}$ 2) of either the test or the reference formulation of acebrophylline HCl in a 2 ${\times}$ 2 crossover study, this was followed by a 1week washout period between either formulation. $AUC_{0-t}$ (the area under the plasma concentration-time curve) was calculated by the linear trapezoidal rule. $C_{max}$ (maximum plasma drug concentration) and $T_{max}$ (time to reach $C_{max}$) were compiled from the plasma concentration-time data. The 90% confidence intervals for the log transformed data were acceptable range of log 0.8 to log 1.25 (e.g., log 0.8964 - log 0.9910 for $AUC_{0-t}$ log 0.8690 - log 1.0750 for $C_{max}$). The major parameters, $AUC_{0-t}$ and $C_{max}$ met the criteria of Korea Food and Drug Administration for bioequivalence indicating that Acephyll$^{(R)}$ capsule (test) is bioequivalent to Surfolase$^{(R)}$ capsule (reference).

• Journal of Environmental Science International
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• v.24 no.11
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• pp.1393-1404
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• 2015

Ten empirical disinfection models for the plasma process were used to find an optimum model. The variation of model parameters in each model according to the operating conditions (first voltage, second voltage, air flow rate, pH, incubation water concentration) were investigated in order to explain the disinfection model. In this experiment, the DBD (dielectric barrier discharge) plasma reactor was used to inactivate Phytophthora capsici which cause wilt in tomato plantation. Optimum disinfection models were chosen among ten models by the application of statistical SSE (sum of squared error), RMSE (root mean sum of squared error), $r^2$ values on the experimental data using the GInaFiT software in Microsoft Excel. The optimum models were shown as Log-linear+Tail model, Double Weibull model and Biphasic model. Three models were applied to the experimental data according to the variation of the operating conditions. In Log-linear+Tail model, $Log_{10}(N_o)$, $Log_{10}(N_{res})$ and $k_{max}$ values were examined. In Double Weibull model, $Log_{10}(N_o)$, $Log_{10}(N_{res})$, ${\alpha}$, ${\delta}_1$, ${\delta}_2$, p values were calculated and examined. In Biphasic model, $Log_{10}(N_o)$, f, $k_{max1}$ and $k_{max2}$ values were used. The appropriate model parameters for the calculation of optimum operating conditions were $k_{max}$, ${\alpha}$, $k_{max1}$ at each model, respectively.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.2
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• pp.397-404
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• 2018

As the usage of internet is increasing, a lot of user behavior are written in a log file and the researches and industries using the log files are getting activated recently. This paper uses the Hadoop based on open source distributed computing platform and proposes a customized tourism system by analyzing user behaviors in the log files. The proposed system uses Google Analytics to get user's log files from the website that users visit, and stores search terms extracted by MapReduce to HDFS. Also it gathers features about the sight-seeing places or cities which travelers want to tour from travel guide websites by Octopus application. It suggests the customized cities by matching the search terms and city features. NBP(next bit permutation) algorithm to rearrange the search terms and city features is used to increase the probability of matching. Some customized cities are suggested by analyzing log files for 39 users to show the performance of the proposed system.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.6
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• pp.135-144
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• 2009

This paper discusses an issue of serious security risks at web log which contains private information, and suggests solutions to protect them. These days privacy is core information to produce value-added in information society. Its scope and type is expanded and is more important along with the growth of information society. Web log is a privacy information file enacted as law in South Korea. Web log is not protected properly in spite of that has private information It just is treated as residual product of web services. Many malicious people could gain private information in web log. This problem is occurred by no classified data and improper development of web application. This paper suggests the technical solutions which control data in development phase and minimizes that the private information stored in web log, and applies in operation environment. It is very efficient method to protect private information and to observe the law.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.681-689
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• 2019

Web usage pattern discovery is an advanced means by using web log data, and it's also a specific application of data mining technology in Web log data mining. In education Data Mining (DM) is the application of Data Mining techniques to educational data (such as Web logs of University, e-learning, adaptive hypermedia and intelligent tutoring systems, etc.), and so, its objective is to analyze these types of data in order to resolve educational research issues. In this paper, the Web log data of a university are used as the research object of data mining. With using the database OLAP technology the Web log data are preprocessed into the data format that can be used for data mining, and the processing results are stored into the MSSQL. At the same time the basic data statistics and analysis are completed based on the processed Web log records. In addition, we introduced the Apriori Algorithm of Web usage pattern mining and its implementation process, developed the Apriori Algorithm program in Python development environment, then gave the performance of the Apriori Algorithm and realized the mining of Web user access pattern. The results have important theoretical significance for the application of the patterns in the development of teaching systems. The next research is to explore the improvement of the Apriori Algorithm in the distributed computing environment.

• Journal of Korea Spatial Information System Society
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• v.5 no.1 s.9
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• pp.39-47
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• 2003

The purpose of this paper is to present the method of acquiring 3D GIS data using the statistical estimating methods of Well Log for balancing Seismic data. We use the reflection coefficients of seismic data to get the parameters for the reservoir characterization and we balance the reflection coefficients of seismic data using well log to increase the confidence of the estimated result. Well logs are required to balance the reflection coefficients at the point where seismic data are acquired. In this research, we discuss the geostatistical estimation methods and we applied these methods to real data. Kriging gives high weights to the close well logs, which means estimated results are mainly affected by close well log. High value of cross variograms gave big difference on cokriging result comparing to kriging results and low value of cross variogram gave little differences.

• Journal of the Korean Geophysical Society
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• v.4 no.2
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• pp.95-102
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• 2001

As a basic study of characterizing fracture condition in bore hole, conventional geophysical well log data consisting of sonic, gamma-gamma and resistivity logs were compared with geological core log and acousic televiewer log in limestone geology. Discontinuities shown on the acoustic televiewer log and the core log show fairly good correlation. The conventional Geophysical log is also shown to bi effective in locating discontinities in limestone geology; sonic log shows the best result and resistivity shows the worst. Particularly, the combination method of density and sonic logs is shown to be the most effective in delineating discontinuities.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.181-184
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• 2000

In this paper, we propose new features for describing texture images by using multi-channel Gabor filter and log-polar transform based on human visual system (HVS). Gabor features are extracted by the mean and standard deviation of energy in Gabor response, followed by Fourier series extension. Log-polar features are extracted by log-polar transform and projection. The proposed texture descriptor performs reasonably well with less number of features than other texture descriptors, which has been verified by experiments using some texture images of MPEG-7 data set.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.151-161
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• 1993

The log-Gumbel distribution in real space is defined by transforming the conventional log-Gumbel distribution in log space. For this model, the parameter estimation techniques are applied based on the methods of moments, maximum likelihood and probability weighted moments. The asymptotic variances of estimator of the quantiles for each estimation method are derived to find the confidence limits for a given return period. Finally, the log-Gumbel model is applied to actual flood data to estimate the parameters, quantiles and confidence limits.