• Journal of the Korean Society of Hazard Mitigation
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• v.9 no.3
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• pp.127-133
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• 2009

In this study, dimensionless-cumulative rainfall curves were generated by multivariate Monte Carlo method. For generation of rainfall curve rainfall storms were divided and made into dimensionless type since it was required to remove the spatial and temporal variances as well as differences in rainfall data. The dimensionless rainfall curves were divided into 4 types, and log-ratio method was introduced to overcome the limitations that elements of dimensionless-cumulative rainfall curve should always be more than zero and the sum total should be one. Orthogonal transformation by Johnson system and the constrained non-normal multivariate Monte Carlo simulation were introduced to analyse the rainfall characteristics. The generative technique in stochastic rainfall variation using multivariate Monte Carlo method will contribute to the design and evaluation of hydrosystems and can use the establishment of the flood disaster prevention system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.241-246
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• 2004

Medical images are being managed more by PACS in general medical institutions. It is important to protect patients from being invaded their privacy related to the images. It is also necessary to confirm the ownership, the right of properity of the medical images and notice whether the data are modified. In this paper, we propose a robust watermarking against RST attacks in medical images on the PACS. The proposed scheme modifies and improves Log-Polar Mapping and Fourier Mellin Transform in order to realize and recover serious image degradation and watermark data loss caused by the conversion between cartesian coordinate and log-polar coordinate. We used the radius and theta Look Up Table to solve the realization of the Fourier Mellin Transform, and inserted a watermark into 2D-DFT magnitudes using Spread Spectrum. Experimental results shows that this method are robust to several attack.

• Journal of Pharmaceutical Investigation
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• v.32 no.3
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• pp.215-221
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• 2002

Cephradine is a first generation cephalosporin and has broad spectrum antibacterial activity against gram-positive and gram-negative microorganisms, through inhibition of bacterial cell wall synthesis. Cephradine is useful for treatment of infections of the urinary and respiratory tract, skin and soft tissues. The purpose of the present study was to evaluate the bioequivalence of two cephradine capsules, Cefradine Yuhan (YuHan Corporation) and Broadcef (Ilsung Pharmaceuticals Co. Ltd.), according to the guidelines of Korea Food and Drug Administration (KFDA). The cephradine release from the two cephradine capsules in vitro was tested using KP VII Apparatus II method with various different kinds of dissolution media (pH 1.2, 4.0, 6.8 buffer solution and water). Twenty normal male volunteers, $23.10{\pm}2.90$ years in age and $67.69{\pm}8.04\;kg$ in body weight, were divided into two groups and a randomized $2{\times}2$ cross-over study was employed. After one capsule containing 500 mg as cephradine was orally administered, blood was taken at predetermined time intervals and the concentrations of cephradine in serum were determined using HPLC method with UV detector. The dissolution profiles of two cephradine capsules were very similar at all dissolution media. Besides, the pharmacokinetic parameters such as $AVC_t,\;C_{max}\;and\;T_{max}$ were calculated and ANOVA test was utilized for the statistical analysis of the parameters using logarithmically transformed $AVC_t\;and\;C_{max}$ and untransformed $T_{max}$. The results showed that the differences in $AVC_t,\;C_{max}\;and\;T_{max}$ between two capsules based on the Cefradine Yuhan were -2.87%, -0.96% and -4.85%, respectively. There were no sequence effects between two capsules in these parameters. The 90% confidence intervals using logarithmically transformed data were within the acceptance range of 1og(0.8) to log(1.25) $(e.g.,\;log(0.93){\sim}log(1.02)\;and\;log(0.88){\sim}log(1.13)\;for \;AVC_t\;and\;C_{max},\;respectively)$. The 90% confidence interval using untransformed data was within ${\pm}20%$ $(e.g., \;-17.54{\sim}7.78\;for\;T_{max})$. All parameters met the criteria of KFDA guideline for bioequivalence, indicating that Broadcef capsule is bioequivalent to Cefradine Yuhan capsule.

• Journal of Korea Water Resources Association
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• v.41 no.8
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• pp.807-823
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• 2008

This paper presents a technique for estimating discharge rating curve parameters. In typical practical applications, the original non-linear rating curve is transformed into a simple linear regression model by log-transforming the measurement without examining the effect of log transformation. The model of pseudo-likelihood estimation is developed in this study to deal with heteroscedasticity of residuals in the original non-linear model. The parameters of rating curves and variance functions of errors are simultaneously estimated by the pseudo-likelihood estimation(P-LE) method. Simulated annealing, a global optimization technique, is adapted to minimize the log likelihood of the weighted residuals. The P-LE model was then applied to a hypothetical site where stage-discharge data were generated by incorporating various errors. Results of the P-LE model show reduced error values and narrower confidence intervals than those of the common log-transform linear least squares(LT-LR) model. Also, the limit of water levels for segmentation of discharge rating curve is estimated in the process of P-LE using the Heaviside function. Finally, model performance of the conventional log-transformed linear regression and the developed model, P-LE are computed and compared. After statistical simulation, the developed method is then applied to the real data sets from 5 gauge stations in the Geum River basin. It can be suggested that this developed strategy is applied to real sites to successfully determine weights taking into account error distributions from the observed discharge data.

• Journal of the Korean Mathematical Society
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• v.54 no.3
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• pp.835-845
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• 2017

The $GCF_{\epsilon}$ expansion is a new class of continued fractions induced by the transformation $T_{\epsilon}:(0, 1]{\rightarrow}(0, 1]$: $T_{\epsilon}(x)={\frac{-1+(k+1)x}{1+k-k{\epsilon}x}}$ for $x{\in}(1/(k+1),1/k]$. Under the algorithm $T_{\epsilon}$, every $x{\in}(0,1]$ corresponds to an increasing digits sequences $\{k_n,n{\geq}1\}$. Their basic properties, including the ergodic properties, law of large number and central limit theorem have been discussed in [4], [5] and [7]. In this paper, we study the large deviation for the $GCF_{\epsilon}$ expansion and show that: $\{{\frac{1}{n}}{\log}k_n,n{\geq}1\}$ satisfies the different large deviation principles when the parameter ${\epsilon}$ changes in [-1, 1], which generalizes a result of L. J. Zhu [9] who considered a case when ${\epsilon}(k){\equiv}0$ (i.e., Engel series).

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1689-1694
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• 2005

Face detection plays an important role in face recognition, video surveillance, and human computer interface. In this paper, we present a face detection system using eye detection with progressive thresholding from a digital camera. The face candidate is detected by using skin color segmentation in the YCbCr color space. The face candidates are verified by detecting the eyes that is located by iterative thresholding and correlation coefficients. Preprocessing includes histogram equalization, log transformation, and gray-scale morphology for the emphasized eyes image. The distance of the eye candidate points generated by the progressive increasing threshold value is employed to extract the facial region. The process of the face detection is repeated by using the increasing threshold value. Experimental results show that more enhanced face detection in real time.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1999.10a
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• pp.99-104
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• 1999

This paper proposes an efficient method constructing a local map using the data of a scanning laser range finder. A laser range finder yields distance data of polar form, that is, distance data corresponding to every scanning directions. So, the data consists of directional angle and distance. We propose a new method to find a line fitting with a set of such data. The method uses Log-Hough Transformation. Usually, map building from these data requires some transformations between different coordinate systems. The new method alleviates such complication. Also, the method simplifies computation for line recognition and eliminates the slope quantization problems inherent in the classical Cartesian Hough transform method. To show the efficiency of the proposed method, it is applied to find a local map using the data from a laser range finder PLS(Proximity Laser Scanner, made by SICK).

• Journal of Information Processing Systems
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• v.11 no.4
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• pp.643-654
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• 2015

Face recognition under controlled settings, such as limited viewpoint and illumination change, can achieve good performance nowadays. However, real world application for face recognition is still challenging. In this paper, we propose using the combination of Affine Scale Invariant Feature Transform (SIFT) and Probabilistic Similarity for face recognition under a large viewpoint change. Affine SIFT is an extension of SIFT algorithm to detect affine invariant local descriptors. Affine SIFT generates a series of different viewpoints using affine transformation. In this way, it allows for a viewpoint difference between the gallery face and probe face. However, the human face is not planar as it contains significant 3D depth. Affine SIFT does not work well for significant change in pose. To complement this, we combined it with probabilistic similarity, which gets the log likelihood between the probe and gallery face based on sum of squared difference (SSD) distribution in an offline learning process. Our experiment results show that our framework achieves impressive better recognition accuracy than other algorithms compared on the FERET database.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.396-403
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• 2014

The multi-divisional knapsack problem is defined as a binary knapsack problem where each mutually exclusive division has its own capacity. In this paper, we present an extension of the multi-divisional knapsack problem that has generalized multiple-choice constraints. We explore the linear programming relaxation (P) of this extended problem and identify some properties of problem (P). Then, we develop a transformation which converts the problem (P) into an LP knapsack problem and derive the optimal solutions of problem (P) from those of the converted LP knapsack problem. The solution procedures have a worst case computational complexity of order $O(n^2{\log}\;n)$, where n is the total number of variables. We illustrate a numerical example and discuss some variations of problem (P).

• Water for future
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• v.7 no.1
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• pp.71-77
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• 1974

This paper reviews several different single site generation models for further development of a model for generating the Synthetic sequences of streamflow in the continuous streams like main streams in Korea. Initially the historical time series is looked using a time series technique, that is correlograms, to determine whether a lag one Markov model will satisfactorily represent the historical data. The single site models which were examined include an empirical model using the historical probability distribution of the random component, the linear autoregressive model(Markov model, or Thomas-Fiering model) using both logarithms of the data and Matala's log-normal transformation equations, and finally gamma distribution model.