• Korea journal of population studies
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• v.11 no.1
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• pp.1-13
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• 1988

This study examines the sampling bias that may have resulted from the large number of missing observations. Despite well-designed and reliable sampling procedures, the observed sample values in DSFH(Demographic Survey on Changes in Family and Household Structure, Japan) included many missing observations. The head administerd survey method of DSFH resulted in a large number of missing observations regarding characteristics of elderly non-head parents and their children. In addition, the response probability of a particular item in DSFH significantly differs by characteristics of elderly parents and their children. Furthermore, missing observations of many items occurred simultaneously. This complex pattern of missing observations critically limits the ability to produce an unbiased analysis. First, the large number of missing observations is likely to cause a misleading estimate of the standard error. Even worse, the possible dependency of missing observations on their latent values is likely to produce biased estimates of covariates. Two models are employed to solve the possible inference biases. First, EM algorithm is used to infer the missing values based on the knowledge of the association between the observed values and other covariates. Second, a selection model was employed given the suspicion that the probability of missing observations of proximity depends on its unobserved outcome.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.475-491
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• 2021

With the recent increase in available high-resolution (< ~1 m) satellite SAR images, the demand for precise registration of SAR images is increasing in various fields including change detection. The registration between high-resolution SAR images acquired in different look angle is difficult due to speckle noise and geometric distortion caused by the characteristics of SAR images. In this study, registration is performed in two stages, coarse and fine, using the x-band SAR data imaged at staring spotlight mode of TerraSAR-X. For the coarse registration, a method combining the adaptive sampling method and SAR-SIFT (Scale Invariant Feature Transform) is applied, and three rigid methods (NCC: Normalized Cross Correlation, Phase Congruency-NCC, MI: Mutual Information) and one non-rigid (Gefolki: Geoscience extended Flow Optical Flow Lucas-Kanade Iterative), for the fine registration stage, was performed for performance comparison. The results were compared by using RMSE (Root Mean Square Error) and FSIM (Feature Similarity) index, and all rigid models showed poor results in all image combinations. It is confirmed that the rigid models have a large registration error in the rugged terrain area. As a result of applying the Gefolki algorithm, it was confirmed that the RMSE of Gefolki showed the best result as a 1~3 pixels, and the FSIM index also obtained a higher value than 0.02~0.03 compared to other rigid methods. It was confirmed that the mis-registration due to terrain effect could be sufficiently reduced by the Gefolki algorithm.

• Korean Journal of Adult Nursing
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• v.19 no.4
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• pp.567-582
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• 2007

Purpose: The purpose of this study was to explore the utilization of the Transtheoretical Model(TTM) for Korean nursing studies on health behaviors and identify the strategies for improvement of further studies. Methods: From a main and seven branch journals on the Korean Society of Nursing Science, a total of 26 studies, which had been conducted based upon the TTM, were selected. The selected studies were analyzed from the September of 2006 to the February of 2007 by the criteria; name of journal, year of publication, health behavior, population, sampling, sample size, research design, instrument (translation process, reliability and validity), and statistical analysis. Results: TTM on the Korean nursing studies was mainly applied for smoking cessation or exercise with elderly or middle aged women. The research findings could not be generalized with the limitation of the use of non representative samples. The most frequently used research design was a cross-sectional survey. Some studies had a lack of reliable and valid instruments, so that the internal validity of the study findings may be threatened. Statistically related problems increased type I error and decreased power. Conclusion: Korean nursing studies based on TTM can be the beginning stage in quality and quantity.

• Analytical Science and Technology
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• v.5 no.3
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• pp.269-276
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• 1992

An ion-exchange/conductometric method is applied for the determination of total acidity in simulated atmospheric samples. Non-$H^+$ cations and strong acid anions are enriched by the preconcentrator columns in series and eluted through the corresponding parallel suppressor units. The conductivities from each channel correspond to the concentrations of the resulting ionized species in equivalents per unit volume. The difference is the measure of acidity due to strong acids. With 5-min sampling at a flow rate of 0.3 mL/min, the detection limits for ${NH_4}^+$ and ${SO_4}^{2-}$ are 0.3 and $0.1{\mu}equiv/L$, respectively. The acidity for samples composed of various ions can be determined without significant error, usually less than 5%. The proposed method discriminates against the artifact from the $CO_2$ dissolution. Principles of acidity measurements are also presented.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.271-277
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• 2010

The randomized response technique is an indirect question that employs a randomizing device to protect respondents' privacy. The technique is now considered the most efficient of the newly developed techniques. In this technique, Chang et al. (2004) suggests an improved forced-answer technique and finds more efficient conditions than Warner did in 1965. But it is the weakness of the technique to lose more information than a direct response technique does. Therefore, a lot of researches have developed new techniques to reduce loss of information, to enhance estimated efficiency, and to efficiently use collected information. Considering this tendency, this paper also tries to improve Chang's technique. It suggests the technique that is extended from Chang's and finds more efficient conditions than Chang's technique and Mangat and Singh's (1990) did.

• Tribology and Lubricants
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• v.36 no.6
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• pp.297-306
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• 2020

This paper reviews studies on the types and functions of oil sensors used for machine condition monitoring. Machine condition monitoring is essential for maintaining the reliability of machines and can help avoid catastrophic failures while ensuring the safety and longevity of operation. Machine condition monitoring involves several components, such as compliance monitoring, structural monitoring, thermography, non-destructive testing, and noise and vibration monitoring. Real-time monitoring with oil analysis is also utilized in various industries, such as manufacturing, aerospace, and power plants. The three main methods of oil analysis are off-line, in-line, and on-line techniques. The on-line method is the most popular among these three because it reduces human error during oil sampling, prevents incipient machine failure, reduces the total maintenance cost, and does not need complicated setup or skilled analysts. This method has two advantages over the other two monitoring methods. First, fault conditions can be noticed at the early stages via detection of wear particles using wear particle sensors; therefore, it provides early warning in the failure process. Second, it is convenient and effective for diagnosing data regardless of the measurement time. Real-time condition monitoring with oil analysis uses various oil sensors to diagnose the machine and oil statuses; further, integrated oil sensors can be used to measure several properties simultaneously.

• Journal of Ecology and Environment
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• v.38 no.4
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• pp.485-491
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• 2015

This study was conducted to develop stem volume models for the volume estimation of Quercus glauca Thunb. in Jeju Island, Republic of Korea. Furthermore, this study validated the developed stem volume models using an independent dataset. A total of 167 trees were measured for their diameter at breast height (DBH), total height and stem volume using non-destructive sampling methods. Eighty percent of the dataset was used for the initial model development while the remaining 20% was used for model validation. The performance of the different models was evaluated using the following fit statistics: standard error of estimate (SEE), mean bias absolute mean deviation (AMD), coefficient of determination (R²), and root mean square error (RMSE). The AMD of the five models from the different DBH classes were determined using the validation dataset. Model 5 (V = aD^bH^c), which estimates volume using DBH and total height as predicting variables, had the best SEE (0.02745), AMD (0.01538), R² (0.97603) and RMSE (0.02746). Overall, volume models with two independent variables (DBH and total height) performed better than those with only one (DBH) based on the model evaluation and validation. The models developed in this study can provide forest managers with accurate estimations for the stem volumes of Quercus glauca in the subtropical forests of Jeju Island, Korea.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.11
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• pp.83-94
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• 2003

In this paper. a highly linear and low glitch CMOS current mode digital-to-analog converter (DAC) by self calibration bias circuit is proposed. The architecture of the DAC is based on a current steering 6＋4 segmented type and new switching scheme for the current cell matrix, which reduced non-linearity error and graded error. In order to achieve a high performance DAC . novel current cell with a low spurious deglitching circuit and a new inverse thermometer decoder are proposed. The prototype DAC was implemented in a 0.35${\mu}{\textrm}{m}$ n-well CMOS technology. Experimental result show that SFDR is 60 ㏈ when sampling frequency is 32MHz and DAC output frequency is 7.92MHz. The DAC dissipates 46 mW at a 3.3 Volt single power supply and occupies a chip area of 1350${\mu}{\textrm}{m}$ ${\times}$750${\mu}{\textrm}{m}$.

• Journal of Computational Design and Engineering
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• v.3 no.3
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• pp.179-190
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• 2016

A kind of modified epoxy resin sheet molding compounds of the impeller has been designed. Through the test, the non-metal impeller has a better environmental aging performance, but must do the waterproof processing design. In order to improve the stability of the impeller vibration design, the influence of uncertainty factors is considered, and a multi-objective robust optimization method is proposed to reduce the weight of the impeller. Firstly, based on the fluid-structure interaction, the analysis model of the impeller vibration is constructed. Secondly, the optimal approximate model of the impeller is constructed by using the Latin hypercube and radial basis function, and the fitting and optimization accuracy of the approximate model is improved by increasing the sample points. Finally, the micro multi-objective genetic algorithm is applied to the robust optimization of approximate model, and the Monte Carlo simulation and Sobol sampling techniques are used for reliability analysis. By comparing the results of the deterministic, different sigma levels and different materials, the multi-objective optimization of the SMC molding impeller can meet the requirements of engineering stability and lightweight. And the effectiveness of the proposed multi-objective robust optimization method is verified by the error analysis. After the SMC molding and the robust optimization of the impeller, the optimized rate reached 42.5%, which greatly improved the economic benefit, and greatly reduce the vibration of the ventilation system.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.3
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• pp.644-653
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• 1998

In resistance spot weld, the assurance of weld quality has been a long-standing problem. Since the weld nuggets if resustance spot welding form between the workpieces, visual detection of defects in usually impossible. Welding quality of resistance spot welding can be verified by non destructive and destructive inspections such as X-Ray inspection and testing of weld strength. But these tests, in addition to being time-consuming and costly, can entail risks due to sampling basis. The purpose of this study is the development of the monitoring system based on fuzzy inference, aimed at diagonosis of quality in resistance spot welding. The fuzzy inference system consists of fuzzy input variables, fuzzy membership functions and fuzzy rules. For inferring the welding quality(strength), the experimental data of the spot welding were acquired in various welding conditions with the monitoring system designed. Some fuzzy input variables-maximum, slop and difference values of electrode movement signals-were extracted from the experimental data. It was confirmed that the fuzzy inference values of strength have a .${\pm}$5% error in comparison with actual values for the selected welding conditions(9-10.5KA, 10-14 cycle, 250-300 $kg_f$). This monitoring system can be useful in improving the quality assurance and reliability of the resistance spot welding process.