• Journal of Korean Society of Environmental Engineers
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• v.34 no.5
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• pp.312-315
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• 2012

In this study, the model which can predict the quality of effluent has been implemented through multiple regression analysis to use operation data of a sewage treatment plant, to which a media process is applied. Multiple regression analysis were carried out by cases according to variable selection method, removal of outliers and log transformation of variables, with using data of one year of 2011. By reviewing the results of predictable models, the accuracy of prediction for $COD_{Mn}$ of treated water of secondary clarifiers was over 0.87 and for T-N was over 0.81. Using this model, it is expected to set the range of operating conditions that do not exceed the standards of effluent quality. In conclusion, the proper guidance on the effluent quality and energy costs within the operating range is expected to be provided to operators.

• Journal of Korean Society of Archives and Records Management
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• v.9 no.1
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• pp.175-196
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• 2009

The government and public institutions are conducting public-opinion surveys as means of drawing the scientific policy decisions throughout the country's whole sectors ; society, culture, welfare, education, etc. The Government Survey Data have been under management by each governmental department, but the improper ways of data collection and management have led to omissions and losses of some data. Also there are limitations on the statistic usage and access to the data due to the fact that the data are managed dispersedly in the form of printed materials. Accordingly, to make the survey data available for the long-term preservation and usage, this study suggests collection policy, standard of evaluation, metadata, the procedure and method of converting materials, preservation format.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.33-49
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• 2000

This research demonstrates the application of GIS to the selection of the waste landfill site through the case study of a urban area. The estimation factors for the suitability analysis of the waste landfill site were determined. The database was built through collection, input, and transformation of data. The recent land cover classification data and NDVI data which were obtained through processing of satellite imagery were incorporated into GIS data as estimation factors. The relative weights of importance among 2nd category estimation factors were determined by the pairwise comparison method. Also relative weights of 1st category estimation factors which are divided into the social-economical factor and the natural environmental factor were combined with those of 2nd category estimation factors. As the results of this case study, the suitability analysis was conducted in accordance with various estimation criteria. The highest suitability index was obtained in the case where we considered the relative weights of 2nd category estimation factors as different in the viewpoint which regards the social economical factor as important.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.199-207
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• 2013

Spin images representing efficiently surface features of 3D mesh models have been used to detect facial landmark points. However, at a certain point, different normal direction can lead to quite different spin images. Moreover, since 3D points are projected to the 2D (${\alpha}-{\beta}$) space during spin image generation, surface features cannot be described clearly. In this paper, we present a method to detect 3D facial landmark using improved spin images by partitioning the search area with respect to angle. By generating sub-spin images for angular partitioned 3D spaces, more unique features describing corresponding surfaces can be obtained, and improve the performance of landmark detection. In order to generate spin images robust to inaccurate surface normal direction, we utilize on averaging surface normal with its neighboring normal vectors. The experimental results show that the proposed method increases the accuracy in landmark detection by about 34% over a conventional method.

• Journal of Korean Society of Archives and Records Management
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• v.20 no.4
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• pp.19-40
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• 2020

Deficiencies are present in records management during the production stage of long-term electronic records preservation. As such, this study seeks to address these issues by introducing Cloud On-Nara System (On-Nara Document 2.0) at records management sites and providing various systems and linked services. In particular, the factors that degrade the continuity of long-term preservation in the records management process, from the production to the utilization of electronic records, in On-Nara Document 2.0 were identified, and the causes were analyzed in compliance with ISO 15486-1:2016 and the Public Records Act. As a result, in redesigning the records management procedure, the organization of the records management hub between systems and the conversion of the document preservation format for long-term preservation were proposed. Moreover, the application of consistent production format selection criteria and the reinforcement of the production and management of granular metadata were recorded. These measures were proposed in an effort to reestablish management methods.

• Journal of Korea Water Resources Association
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• v.47 no.5
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• pp.469-482
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• 2014

This study developed a Bayesian spatial regional frequency analysis, which aimed to analyze spatial patterns of design rainfall by incorporating geographical information (e.g. latitude, longitude and altitude) and climate characteristics (e.g. annual maximum series) within a Bayesian framework. There are disadvantages to considering geographical characteristics and to increasing uncertainties associated with areal rainfall estimation on the existing regional frequency analysis. In this sense, this study estimated the parameters of Gumbel distribution which is a function of geographical and climate characteristics, and the estimated parameters were spatially interpolated to derive design rainfall over the entire Han-river watershed. The proposed Bayesian spatial regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis, and even better performance in terms of quantifying uncertainty of design rainfall and considering geographical information as a predictor.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1009-1018
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• 2017

We developed new Digital Sampler for KVN(: Korean VLBI Network). The sampler has 1024MHz sampling frequency with 2bits/sample. The sampler's input reference frequencies are 1pps(: pulse per second) and 10MHz, also UTC(: Universal Time Coordinated) time information out with 1PPS signal, synchronized. The output of sampling data is adapted VSI(: VLBI Standard Interface) specification including the time information. In order to confirm the performance of the sampler, we carried out the astronomical radio observation test in Ulsan Radio Observatory of KVN. It was confirmed the stable performance. In this paper, We introduce the new developed sampler and present the observational test result.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1239-1247
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• 2015

In this study, 64 administrative regions with high frequencies of apartment trade in Seoul, Korea are classified by the apartment sale price. To consider distributions of apartment price for each region as well as the mean of the price, the symbolic histogram-valued data approach is employed. Symbolic data include all types of data which have internal variation in themselves such as intervals, lists, histograms, distributions, and models, etc. As a result of the cluster analysis using symbolic histogram data, it is found that Gangnam, Seocho, and Songpa districts and regions near by those districts have relatively higher prices and larger dispersions. This result makes sense because those regions have good accessibility to downtown and educational environment.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.279-289
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• 2010

In this study, we propose a simple statistical model for determining the admission or discharge of 668 patients with a chief complaint of dyspnea. For this, we use 11 explanatory variables which are chosen to be important by clinical experts among 55 variables. As a modification process, we determine the discharge interval of each variable by the kernel density functions of the admitted and discharged patients. We then choose the optimal model for determining the discharge of patients based on the number of explanatory variables belonging to the corresponding discharge intervals. Since the numbers of the admitted and discharged patients are not balanced, we use, as the criteria for selecting the optimal model, the arithmetic mean of sensitivity and specificity and the harmonic mean of sensitivity and precision. The selected optimal model predicts the discharge if 7 or more explanatory variables belong to the corresponding discharge intervals.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.383-393
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• 2017

When we deal with grouped statistical data, it is desirable to use a calculation method that gives as close value to the true value of a statistic as possible. In this paper, we suggested a new method to calculate the quantiles of grouped data. The main idea of the suggested method is calculating the data values by partitioning the pentagons, that correspond to the class intervals in the frequency polygon drawn according to the histogram, into parts with equal area. We compared this method with existing methods through simulations using some datasets from introductory statistics textbooks. In the simulation study, we simulated as many data values as given in each class interval using the inverse transform method, on the basis of the distribution that has the shape given by the frequency polygon. Using the sum of squares of differences from quantiles of the simulated data as a criterion, the suggested method was found to have better performance than existing methods for almost all quartiles and deciles.