• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.78-85
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• 1996

The set of admissible time-variations in the input signal can be separated into two categories : slow parameter changes and large parameter changes which occur infrequently. A common approach used in the tracking of slowly time-varying parameters is the exponential recursive least-squares(RLS) algorithm. There have been a variety of research works on the error analysis of the exponential RLS algorithm for the slowly time-varying parameters. In this paper, the focus has been given to the error analysis of exponential RLS algorithms for the input data with abrupt property changes. The voiced speech signal is chosen as the principal application. In order to analyze the error performance of the exponential RLS algorithm, deterministic properties of the exponential RLS algorithms is first analyzed for the case of abrupt parameter changes, the impulsive input(or error variance) synchronous to the abrupt change of parameter vectors actually enhances the convergence of the exponential RLS algorithm. The analysis has also been verified through simulations on the synthetic speech signal.

• Journal of Family Resource Management and Policy Review
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• v.4 no.1
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• pp.15-28
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• 2000

The purpose of this study was to examine the knowledge about savings of customers who utilize Investment Trust Company and to analyze the factors affecting it. The data for the analysis were collected by structured questionnaires and consisted of 191 customers who utilize Investment Trust Company. Descriptive. Descriptive Statistics including percentage, frequency, means, and standard derivation, t-test, one-way ANOVA with Scheffe test, multiple regression analysis were used to analyze the data. The following is a summary of major findings. 1) The customers knowledge about savings showed generally low-level. Especially the knowledge about tax and regulation of savings were the areas shown the lowest level. 2) The age, marital status, education and occupation of customers and total period of utilizing company were the factors affecting the knowledge of customers in the one-way ANOVA analysis. 3) The result of regression analysis indicated that age of customers and total periods of utilizing company were the significant predictors of customers’knowledge. These two variables explained 25.77% of variance of customers’knowledge about savings.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.11 no.2
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• pp.220-225
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• 2004

Purpose: The purpose of this study was to test the reliability and validity of FAI and to apply it in Korea. Method: Data were collected from 180 middle-age women. The questionnaire, which was originally developed by Schwartz, Jandorf & Krupp, was analyzed using Cronbach's a and factor analysis. Results: Cronbach's a for the FAI was .9198. As a result of item analysis, 27 items were selected from the total of 29 items, Items that showed low correlation with the total scale were excluded. Six factors were fixed from the data analysis performed using principle component analysis and varimax rotation. These six factors account for 65.3% of total variance. The first factor was global fatigue severity, and the second one was fatigue consequences. The other factors were method of fatigue reduction, fatigue caused by exercise, fatigue caused by routine activity, and fatigue caused by stress and depression, sequentially. Conclusion: The reliability and validity of FAI were verified.

• Proceedings of the Korean Geotechical Society Conference
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• 2005.10a
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• pp.344-351
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• 2005

In this paper, a reliability-groundwater flow program is developed by coupling the 2-D finite element numerical groundwater flow program with first and second order reliability program. From the parametric study of hydraulic conductivity of soil layers, the increase of both mean and variance of hydraulic conductivity results in the increase of probability of exceeding the threshold hydraulic head. The probability of failure was more sensitive to parameters of weathered granitic soil and rock located at the middle and bottom of the excavation than those at the other locations. It can be recommended from this study that the reliability method, which can include the uncertainty of soil parameters, should be performed together with the deterministic analysis to compensate the weakness of the latter analysis for the groundwater flow problem of underground excavations.

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.4
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• pp.602-607
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• 1993

Concept of the comfort and fitness becomes a major concern in the basic function of the ready-made clothes. This research was performed to classify and characterize Korean adult males anthropometrically. Sample size was 1290 subjects and their age range was from 19 to 54 years old. Sampling was carried out by the stratified sampling method. 75 variables in total were applied to classify the bodytypes. Data were analyzed by the multivariate method, especially factor and cluster analysis. The high factor loading items extracted by factor analysis were based to determine the variables of the cluster analysis for the similar bodytypes respectively. In the part of the lower body, 14 variables from the data were applied to classify the bodytypes of lower part by Ward's minimum variance method. The group fanning a cluster were subdivided into 5 sets by cross-tabulation extracted by the hierarchical cluster analysis. Type 3 and 4 in lower body were composed of the majority of 53.1% of the subjects. The Korean adult males had relatively well-balanced in lower body.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.197-200
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• 2008

A GNSS augmentation system provides precise position information using corrected GNSS pseudorange measurements. Common bias errors are corrected by PRC (Pseudorange Correction) between reference stations and a rover. However non-common errors (Ionospheric and Tropospheric noise error) are not corrected. Using position error variance this paper analyzes non-common errors (noise errors) of ionosphere and troposphere wet vapor.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.55-61
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• 2010

In this paper, we proposed selective extraction method of frequency information and PCA-ELM based diagnosis system for three-phase induction motors. As the first step for diagnosis procedure, DFT is performed to transform the acquired current signal into frequency domain. And then, frequency components are selected according to discriminate order calculated by variance As the next step, feature extraction is performed by principal component analysis (PCA). Finally, we used the classifier based on Extreme Learning Machine (ELM) with fast learning procedure. To show the effectiveness, the proposed diagnostic system has been intensively tested with the various data acquired under different electrical and mechanical faults with varying load.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1045-1050
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• 2008

A GNSS augmentation system provides precision information using corrected GNSS pseudorange measurements. Common bias errors are corrected by PRC (Pseudorange Correction) between reference stations and a rover. However non-common errors (ionospheric and tropospheric noise error) are not corrected. Using position error variance this paper analyzes non-common error (noise errors) of ionosphere and troposphere wet vapor.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2001.10a
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• pp.150-153
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• 2001

The present work concerns optimal design for the injection molding process of a deflection yoke (coil separator). The optimal design for the injection molding process is developed using design of experiments and finite element analysis. Two design of experiments approaches are applied such as: the design of experiment for mold design and the design the experiments for determination of process parameters. Finite element analyses have been carried out as a design of experiments for mold design: runner system and cooling channel. In order to determine optimal process experiments have been performed for various process conditions with the design of experiments scheduling.

• Journal of the Korean Society of Safety
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• v.21 no.1 s.73
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• pp.21-27
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• 2006

In this paper, object of experiment is to study on the effect parameters to obtain optimal surface roughness in face turning. Surface roughness is significantly important to be high quality of parts produced by turning process. For this purpose, the optimization of cutting parameters for face turning operation is investigated applying the Taguchi method. An orthogonal array, signal-to-noise, and the analysis of variance are employed to evaluate effect of cutting parameters for face turning. Also confirmation tests were performed to make a comparison between the results predicted from the mentioned correlations and the theoretical results. Cutting experiment is performed without cutting fluid using coated tungsten carbide insert about workpiece of SM45C. And regression analysis technique has been used to study the effects of the cutting parameters.