• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.471-483
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• 2012

One of the most important problems in cluster analysis is the selection of variables that truly define cluster structure, while eliminating noisy variables that mask such structure. Brusco and Cradit (2001) present VS-KM(variable-selection heuristic for K-means clustering) procedure for selecting true variables for K-means clustering based on adjusted Rand index. This procedure starts with the fixed number of clusters in K-means and adds variables sequentially based on an adjusted Rand index. This paper presents an updated procedure combining the VS-KM with the automated K-means procedure provided by Kim (2009). This automated variable selection procedure for K-means clustering calculates the cluster number and initial cluster center whenever new variable is added and adds a variable based on adjusted Rand index. Simulation result indicates that the proposed procedure is very effective at selecting true variables and at eliminating noisy variables. Implemented program using R can be obtained on the website "http://faculty.knou.ac.kr/sskim/nvarkm.r and vnvarkm.r".

• ETRI Journal
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• v.4 no.3
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• pp.18-29
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• 1982

In a block adaptive filtering procedure, the filter coefficients are adjusted once per each output block while maintaining performance comparable to that of widely used LMS adaptive filtering in which the filter coefficients are adjusted once per each output data sample. An efficient implementation of block adaptive filter is possible by means of discrete transform technique which has cyclic convolution property and fast algorithms. In this paper, the block adaptive filtering using Fermat Number Transform (FNT) is investigated to exploit the computational efficiency and less quantization effect on the performance compared with finite precision FFT realization. And this has been verified by computer simulation for several applications including adaptive channel equalizer and system identification.

• Journal of Preventive Medicine and Public Health
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• v.13 no.1
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• pp.27-34
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• 1980

Purpose of this study is to find out proper means of estimating the urinary mercury excretion in the normal individuals. Whole void volume was collected every 2 hours beginning from 6 o'clock in the morning until 6 o'clock next morning. Mercury excretion in each urine specimen was measured by NIOSH recommended dithizone colorimetric method (Method No.: P & CAM 145). Urinary concentration of mercury was adjusted by two means: specific gravity of 1.024 and a gram of creatinine excretion per liter of urine comparing the data with the unadjusted ones. Mercury excretion in 24-hour urine specimen was calculated by adding the amounts measured with the hourly collected specimens of each individual. Statistical analysis of the urinary mercury excretion revealed the following results: 1. Frequency distribution curve of mercury excreted in urine of hourly specimens was best fitted to power function expressed in the form of $y=ax^b$. Adjustment of the urinary mercury concentration by creatinine excretion was shown to be superior($y=1674x^{-1.52},\;r^2=0.95$) over nonadjustment($y=2702x^{-1.57},\;r^2=0.92$) and adjustment by specific gravity of 1.024($y=4535x^{-1.66},\;r^2=0.93$). 2. Both log-transformed mercury excretion in hourly voided specimens and mercury excretion itself in 24 hour specimens showed the normal distributions. 3. The frequency distribution of mercury adjusting the urinary concentration of mercury by creatinine excretion was best fitted to a theoretical normal distribution with the sample means and standard deviation than those unadjusted or adjusted with specific gravity of 1.024. 4. Average urinary mercury excretions in 24-hour urine specimen in an individual were as follows: a) Unadjusted mercury excretion mean and standard deviation : $$18.6{\pm}13.68{\mu}gHg/l$$. median : $$16.0\;{\mu}gHg/l$$. range : $$0.0-55.10\;{\mu}gHg/l$$. b) Adjusted with specific gravity mean : $$20.7{\pm}11.76\;{\mu}gHg/l{\times}\frac{0.024}{S.G-1.000}$$ median : $$20.7\;{\mu}gHg/l{\times}\frac{0.024}{S.G-1.000}$$ range : $$0.0-52.9\;{\mu}gHg/l{\times}\frac{0.024}{S.G-1.000}$$ c) Adjusted with creatinine excretion mean and standard deviation : $$10.5{\pm}6.98\;{\mu}gHg/g$$ creatinine/l median : $$9.4\;{\mu}gHg/g$$ creatinine/l range : $$0.0-26.7\;{\mu}gHg/g$$ creatinine/l 5. No statistically significant differences were found between means calculated from 24-hour urine specimens and those from hourly specimens transformed into logarithmic values. (P<0.05).

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.55-67
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• 2015

An important problem in cluster analysis is the selection of variables that define cluster structure that also eliminate noisy variables that mask cluster structure; in addition, outlier detection is a fundamental task for cluster analysis. Here we provide an automated K-means clustering process combined with variable selection and outlier identification. The Automated K-means clustering procedure consists of three processes: (i) automatically calculating the cluster number and initial cluster center whenever a new variable is added, (ii) identifying outliers for each cluster depending on used variables, (iii) selecting variables defining cluster structure in a forward manner. To select variables, we applied VS-KM (variable-selection heuristic for K-means clustering) procedure (Brusco and Cradit, 2001). To identify outliers, we used a hybrid approach combining a clustering based approach and distance based approach. Simulation results indicate that the proposed automated K-means clustering procedure is effective to select variables and identify outliers. The implemented R program can be obtained at http://www.knou.ac.kr/~sskim/SVOKmeans.r.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.490-495
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• 2006

The analysis method proposed by PCA is widely used in calculating the column shortening of reinforced and composite columns of a tall building. However, residual creep factor which relates creep strain of reinforced concrete to creep strain of plain concrete is based on Rate of Creep Method (RCM) which has theoretical defects and is considered obsolete. In this paper, a new equation for the residual creep factor based on Age-adjusted Effective Modulus Method (AEMM) which is considered exact and better than RCM is proposed. The residual creep factor by RCM is found to be higher than one by AEMM, which means current PCA method overestimates the shortening of a reinforced concrete column. By using the residual creep factor by AEMM, more exact column shortening of a tall building can be obtainable with a simple modification to PCA method.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.721-729
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• 2012

Various methods control the influence of a covariate on a response variable. These methods are analysis of covariance(ANCOVA), RANK ANCOVA, ANOVA of (covariate-adjusted) residuals, and Kruskal-Wallis tests on residuals. Covariate-adjusted residuals are obtained from the overall regression line fit to the entire data set that ignore the treatment levels or factors. It is demonstrated that the methods on covariate-adjusted residuals are only appropriate when the regression lines are parallel and covariate means are equal for all treatments. In this paper, we proposed the new nonparametric method on the ANCOVA model, as applying joint placement in a one-way layout on residuals as described in Chung and Kim (2007). A Monte Carlo simulation study is adapted to compare the power of the proposed procedure with those of the previous procedure.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1244-1248
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• 2005

In this paper, we propose fuzzy c-means (FCM) to solve recognition errors in invariant range image, multi-pose face recognition. Scale, center and pose error problems were solved using geometric transformation. Range image face data was digitized into range image data by using the laser range finder that does not depend on the ambient light source. Then, the digitized range image face data is used as a model to generate multi-pose data. Each pose data size was reduced by linear reduction into the database. The reduced range image face data was transformed to the gradient face model for facial feature image extraction and also for matching using the fuzzy membership adjusted by fuzzy c-means. The proposed method was tested using facial range images from 40 people with normal facial expressions. The output of the detection and recognition system has to be accurate to about 93 percent. Simultaneously, the system must be robust enough to overcome typical image-acquisition problems such as noise, vertical rotated face and range resolution.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.4
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• pp.363-367
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• 2015

This paper reports on thermally adjusted graphene oxide (GO) as the hole transport layer (HTL) for organic light-emitting diodes (OLEDs). GO is generally not suitable for HTL of OLEDs because of intrinsic specific resistance. In this paper, the specific resistance of GO is adjusted by the thermal annealing process. The optimum specific resistance of HTL is found to be $10^2{\Omega}{\cdot}m$, and is defined by the maximum current efficiency of OLEDs, 2 cd/A. In addition, the reasons for specific resistance change are identified by x-ray photoelectron spectroscopy (XPS). First, the XPS results show that several functional groups of GO were detached by thermal energy, and the amount of epoxide changed substantially following the temperature. Second, the full width at half maximum (FWHM) of the C-C bond decreased during the process. That means the crystallinity of the graphene improved, which is the scientific basis for the change in specific resistance.

• Journal of the Korean Ceramic Society
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• v.31 no.3
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• pp.291-297
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• 1994

Cordierite powders were prepared by controlled hydrolysis of metal alkoxides with catalysts in water medium without using organic solvents. Water was adjusted to a certain pH by HC1 and NH4OH. $\alpha$-Cordierite powder was prepared from aluminum isopropoxide, tetraethyl orthosilicate and magnesium ethoxide mixed with water adjusted to pH of 3. At water pH of 11, $\alpha$-cordierite, mullite and $\beta$-quartz phases were coexisted. The powders were freeze dried, calcined and then fired at different temperatures. The characteristics of powders were examined by means of DTA, X-ray diffraction, FT-IR, and electron microscopy. It was found that $\alpha$-cordierite could be synthesized at temperature of 120$0^{\circ}C$ from the powders prepared by alkoxides with water medium without organic solvents.

• Earthquakes and Structures
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• v.22 no.1
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• pp.83-94
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• 2022

In recent years, some studies have identified and quantified factors that can increase or decrease the seismic vulnerability of buildings. These modifier factors, related to the building characteristics and condition, are taken into account in the vulnerability assessment, by means of a numerical estimation resulting from the quantification of these modifiers through vulnerability indexes. However, views have differed on the definition and the quantification of modifiers. In this study, modifier parameters and scores of the Risk-UE Level 1 method are adjusted based on the Algerian seismic code recommendations and the reviews proposed in the literature. The adjusted modifiers and scores are applied to reinforced concrete (RC) buildings in Boumerdes city, in order to assess probable seismic damage. Comparison between estimated damage and observed damage caused by the 2003 Boumerdes earthquake is done, with the objective to (i) validate the model involving influence of the modifier parameters on the seismic vulnerability, and (ii) to define the relationship between modifiers and damage. This research may help planners in improving seismic regulations and reducing vulnerability of existing buildings.