• Journal of Korea Water Resources Association
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• v.49 no.8
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• pp.645-656
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• 2016

The study performed a regional flood frequency analysis and proposed a regression equation to estimate design floods corresponding to return periods for ungauged basins in Geum-river basin. Five preliminary tests were employed to investigate hydrological independence and homogeneity of streamflow data, i.e. the lag-one autocorrelation test, time homogeneity test, Grubbs-Beck outlier test, discordancy measure test ($D_i$), and regional homogeneity measure (H). The test results showed that streamflow data were time-independent, discordant and homogeneous within the basin. Using five probability distributions (generalized extreme value (GEV), three-parameter log-normal (LN-III), Pearson type 3 (P-III), generalized logistic (GLO), generalized Pareto (GPA)), comparative regional flood frequency analyses were carried out for the region. Based on the L-moment ratio diagram, average weighted distance (AWD) and goodness-of-fit statistics ($Z^{DIST}$), the GLO distribution was selected as the best fit model for Geum-river basin. Using the GLO, a regression equation was developed for estimating regional design floods, and validated by comparing the estimated and observed streamflows at the Ganggyeong station.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.99-110
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• 2011

Mobile environments rapidly changing and digital convergence widely employed, mobile devices including smart phones have been playing a critical role that changes users' lifestyle in the areas of entertainments, businesses and information services. The various services using mobile devices are developing to meet the personal needs of users in the mobile environments. Especially, an LBS (Location-Based Service) is combined with other services and contents such as augmented reality, mobile SNS (Social Network Service), games, and searching, which can provide convenient and useful services to mobile users. In this paper, we design and implement the prototype of mobile personal assistant (PA) agents. Our personal assistant agent helps users do some tasks by hiding the complexity of difficult tasks, performing tasks on behalf of the users, and reflecting the preferences of users. To identify user's preferences and provide personalized services, clustering and classification algorithms of data mining are applied. The clusters of the log data using clustering algorithms are made by measuring the dissimilarity between two objects based on usage patterns. The classification algorithms produce user profiles within each cluster, which make it possible for PA agents to provide users with personalized services and contents. In the experiment, we measured the classification accuracy of user model clustered using clustering algorithms. It turned out that the classification accuracy using our method was increased by 17.42%, compared with that using other clustering algorithms.

• Journal of The Korean Society of Grassland and Forage Science
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• v.37 no.4
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.43 no.5
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• pp.415-420
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• 2010

In Korea, oysters are used as an ingredient of Kimchi (Korean pickled cabbage) in early winter. Although viral contamination of oysters, including contamination by norovirus, can provoke gastroenteric illness, little is known of the epidemiological relationship to outbreaks. We postulated that Kimchi ripening can reduce the infectivity of norovirus, in order to test this hypothesis, we carried out a model experiment. Since norovirus is currently regarded as non-culturable, feline calicivirus (FCV) was used as a surrogate to examine the activation of norovirus with Kimchi ripening. In commercial well-prepared Kimchi, the infectivity ($TCID_{50}$) of FCV decreased by 2 log every 12 hours and reached the limit of detection after 48 hours during over-aging at $25^{\circ}C$. During storage at $4^{\circ}C$, the infectivity ($TCID_{50}$) of FCV decreased slowly and reached 5.00 $TCID_{50}$ after 48 hours. The low pH appears to affect the infectivity of FCV directly via organic acids produced by ripening during over-aging and storage. In neutralized lab-prepared Kimchi (pH 7.0), the infectivity ($TCID_{50}$) of FCV also decreased and reached the limit of detection after 72 hours at $4^{\circ}C$. This indicates that there are substances beside organic acids in Kimchi that originate from the raw materials and are produced during ripening. Among the raw materials, salt-fermented anchovies and garlic showed high direct antiviral activity. The main factor decreasing the infectivity of FCV in Kimchi was the high acidity caused by organic acids, regardless of the type, produced by ripening. Furthermore, unknown secondary products of microorganisms associated with Kimchi ripening and antiviral materials originating from raw material might contribute to the decreased infectivity of FCV, the surrogate of norovirus.

• Korea journal of population studies
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• v.26 no.2
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• pp.33-62
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• 2003

The purpose of this study is to analyze the relative importance of three factor -socioeconomic development, public health development, egalitarian nature of socioeconomic development- affecting mortality declines. Infant mortality rate and life expectancy at birth are used as the mortality index, that is the dependent variables, while GNP is used as the indicator of socioeconomic development, primary school enrollment ratio of female as the indicator of egalitarian nature of socioeconomic development, population per hospital bed as the indicator of public health. The data of these variables are collected two time-periods -before 1970 and during 1970-1980- over 50 countries. The explanatory data analysis is used as the statistical technique. We can find whether the relationship between dependent variable and independent variables are linear or nonlinear, and which case is the influential case in our model. The main results of this study are followings. First, the association between infant mortality rates and four indices are not linear. The most important factor explaining the variation of infant mortality is GNP, while primary enrollment of female is the second and GINI is the third important factor. However, population per hospital bed does not have a significant effect on the infant mortality rates in this study. Second, life expectancy at birth is log-linearly related to GNP. Unlike infant mortality rates, the most important factor explaining the variation of life expectance at birth is women's education and the next important factor GNP, and then the third one GINI. But, still population per hospital bed is not significantly related to the variation of life expectance in this study.

• Applied Biological Chemistry
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• v.29 no.3
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• pp.324-330
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• 1986

The responses of brain acetylcholinesterase(Ach-E) and plasma cholinesterase (Ch-E) activities were studied in chicknes given oral doses of Terbufos(S-tert-butyl thiomethyl 0,0-diethyl phosphorodithioate), an organophosphorus insecticide. The acute oral $LD_{50}$ of terbufos was 1.82mg/kg. The activity of plasma Ch-E was inhibited more rapidly than that of brain Ach-E, whereas recovery of plasma Ch-E activity was more rapid than that of brain Ach-E. Recovery of brain Ach-E and plasma Ch-E was followed the model $Y=a+b(log_{10}X)$. Brain Ach-E activity and plasma Ch-E were inhibited 83% and 94%, respectively, at 60min after administered oral $LD_{50}$. Brain Ach-E and plasma Ch-E was inhibited in vitro by Terbufos

• Korean Journal of Construction Engineering and Management
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• v.19 no.1
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• pp.21-31
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• 2018

The rapid increase of the elderly living alone is a critical issue in worldwide as it leads to a rapid increase of a social support costs (e.g., medical expenses) for the elderly. In early stages of dementia, the activities of daily living (ADL) including self-care tasks can be affected by abnormal patterns or behaviors and used as an evidence for the early diagnosis. However, extracting activities using non-intrusive approach is still quite challenging and the existing methods are not fully visualized to understand the behavior pattern or routine. To address these issues, this research suggests a model to extract the activities from coarse-grained data (spatio-temporal data log) and visualize the behavioral context information. Our approach shows the process of extracting and visualizing the subject's spaceactivity map presenting the context of each activity (time, room, duration, sequence, frequency). This research contributes to show a possibility of detecting subject's activities and behavioral patterns using coarse-grained data (limited to spatio-temporal information) with little infringement of personal privacy.

• Journal of the Korea Society of Computer and Information
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• v.12 no.1 s.45
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• pp.161-168
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• 2007

Web attack uses structural, logical and coding error or web application rather than vulnerability to Web server itself. According to the Open Web Application Security Project (OWASP) published about ten types of the web application vulnerability to show the causes of hacking, the risk of hacking and the severity of damage are well known. The detection ability and response is important to deal with web hacking. Filtering methods like pattern matching and code modification are used for defense but these methods can not detect new types of attacks. Also though the security unit product like IDS or web application firewall can be used, these require a lot of money and efforts to operate and maintain, and security unit product is likely to generate false positive detection. In this research profiling method that attracts the structure of web application and the attributes of input parameters such as types and length is used, and by installing structural database of web application in advance it is possible that the lack of the validation of user input value check and the verification and attack detection is solved through using profiling identifier of database against illegal request. Integral security management system has been used in most institutes. Therefore even if additional unit security product is not applied, attacks against the web application will be able to be detected by showing the model, which the security monitoring log gathering agent of the integral security management system and the function of the detection of web application attack are combined.

• Journal of Korea Water Resources Association
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• v.51 no.9
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• pp.747-759
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• 2018

Multivariate regional frequency analysis has advantages of regional and multivariate framework as adopting a large number of regional dataset and modeling phenomena that cannot be considered in the univariate frequency analysis. To the best of our knowledge, the multivariate regional frequency analysis has not been employed for hydrological variables in South Korea. Applicability of the multivariate regional frequency analysis should be investigated for the hydrological variable in South Korea in order to improve our capacity to model the hydrological variables. The current study focused on estimating parameters of regional copula and regional marginal models, selecting the most appropriate distribution models, and estimating regional multivariate growth curve in the multivariate regional frequency analysis. Annual maximum rainfall and duration data observed at 71 stations were used for the analysis. The results of the current study indicate that Frank and Gumbel copula models were selected as the most appropriate regional copula models for the employed regions. Several distributions, e.g. Gumbel and log-normal, were the representative regional marginal models. Based on relative root mean square error of the quantile growth curves, the multivariate regional frequency analysis provided more stable and accurate quantiles than the multivariate at-site frequency analysis, especially for long return periods. Application of regional frequency analysis in bivariate rainfall-duration analysis can provide more stable quantile estimation for hydraulic infrastructure design criteria and accurate modelling of rainfall-duration relationship.

• Journal of the Korean Institute of Landscape Architecture
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• v.14 no.2
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• pp.81-90
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• 1986

The full grasp of recreation demand and factors affecting on recreation demand can be very important information for park planning and management. The object-tives of this study are to investigate factors affecting the fluctuation of urban park visitors and to analyze the relationship between these factors and the daily parti-cipations. The results were as follows; 1) The peak of monthly participations comes on May, April, August and October in order. And these months are specified as school picnic period and vacation of school children. 2) In correlation analysis, the variables such as ‘Day of a week(D)’, ‘Monthly mean temp.(T)’and ‘Monthly character(M)’have high correlations with ‘No. of visitors’in order. And it is better to categorize months by its charater(picnic period in school, vacation etc) than by seasons. 3) Candidate regression model were established, as for 1984 log U= 1.51 + 0.64D1 + 0.02T + 0.36W1 - 0.23M4 + 0.003SS + 0.24Ml($R^2$=0.5326) where, U=no. of daily visitors D1 = sunday.ho1iday(1), weekday(0) T=monthly mean temperature($^{\circ}C$) W1= weather (sunny.cloudy(1) , rainy (>5mm)(0)> M4=non vacations and non school picnic period(1) , if not (0) SS=monthly sunshining hours M1=summer vacation(1), if not(0) 4) The most important variable was ‘Day of a week’(sunday.holiday or not). And temperature, weather and monthly charcter(especially picnic period of school and vacation) were in turn, hence ‘Children's grand park’shows the use pattern of park.