• Korean Journal of Materials Research
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• v.34 no.2
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• pp.105-110
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• 2024

Scanning probe microscopy (SPM) has become an indispensable tool in efforts to develop the next generation of nanoelectronic devices, given its achievable nanometer spatial resolution and highly versatile ability to measure a variety of properties. Recently a new scanning probe microscope was developed to overcome the tip degradation problem of the classic SPM. The main advantage of this new method, called Reverse tip sample (RTS) SPM, is that a single tip can be replaced by a chip containing hundreds to thousands of tips. Generally for use in RTS SPM, pyramid-shaped diamond tips are made by molding on a silicon substrate. Combining RTS SPM with Scanning spreading resistance microscopy (SSRM) using the diamond tip offers the potential to perform 3D profiling of semiconductor materials. However, damage frequently occurs to the completed tips because of the complex manufacturing process. In this work, we design, fabricate, and evaluate an RTS tip chip prototype to simplify the complex manufacturing process, prevent tip damage, and shorten manufacturing time.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1998.03a
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• pp.160-167
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• 1998

This article is aimed primarily at establishing a process planning method for complex circular shells. For the deep drawing of complex shaped shell, the optimum process design is required to reduce the trial cost, improve the quality, increase the productivity and shorten the delivery. The present approach which is related to the optimum process planning is based on the empirical knowledge through trial and error in the industrial field. In order to check the validity and the effectiveness of proposed work, a sample process design has been applied to the multi-stepped deep drawing of complex shell considering the process variables such as drawing rate, radius and blank development. In particular, the difference between the limiting drawing rate and the optimum drawing rate has been discussed and has been shown the usefulness of present suggestion.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1155-1167
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• 2009

We made a new sample design for life and consciousness survey of Kyungpook people in 2007. We used the 10% sample survey data of 2005 population and housing census as a survey population. After stratification, we allocate proportionally samples within strata after examining various characteristics in previous survey, which includes economic activity state, an income level per year, and housing possession. And we calculated weight in a new sample design and derived estimators and a formula of standard error using the weights.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1217-1225
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• 2015

Survey research, data is commonly collected through a sample design with complex design features that allow the relative efficiency on the precision of an estimator to be measured using the concept of the design effect compared to simple random sampling as a reference design. This concept is most useful when the design effect can be expressed as a function of various design features. We propose a design effect formula suitable under a stratified multistage sampling by generalizing Gabler et al. (1999, 2006)'s approaches for multistage sampling. Its use can either guide improvement in the design efficiency when in design stage or enable the evaluation of the adopted design features afterwards.

• Survey Research
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• v.11 no.1
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• pp.123-144
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• 2010

In new sample design for Korea Housing Survey to research about housing policy, total strata are forty five because individual results of sixteen regions are estimated. The sample size is determined by sample errors of several variables which are the living area, family income, householder income, and living expenses. The sample size of each region is determined by relative standard error of existing result, and the strata sample size is to use the square root proportion allocation. Enumeration districts are sampled by the probability proportion to size systematic sampling in proportion to the enumeration district size, and the systemic sampling to use assortment characteristics. We considered a new apartment complex because of variation reflections which are rebuilder and redevelopment of houses. To get estimators of mean and variance, we used the design weighting, non-response adjusting, and post-stratification. In order to consider estimation efficiency, we calculate the design effect using estimators of variance.

• Journal of Veterinary Clinics
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• v.32 no.1
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• pp.73-77
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• 2015

There has been increasing attention on sample size requirements in peer reviewed medical literatures. Accordingly, a statistically-valid sample size determination has been described for a variety of medical situations including diagnostic test accuracy studies. If the sample is too small, the estimate is too inaccurate to be useful. On the other hand, a very large sample size would yield the estimate with more accurate than required but may be costly and inefficient. Choosing the optimal sample size depends on statistical considerations, such as the desired precision, statistical power, confidence level and prevalence of disease, and non-statistical considerations, such as resources, cost and sample availability. In a previous paper (J Vet Clin 2012; 29: 68-77) we briefly described the statistical theory behind sample size calculations and provided practical methods of calculating sample size in different situations for different research purposes. This review describes how to calculate sample sizes when assessing diagnostic test performance such as sensitivity and specificity alone. Also included in this paper are tables and formulae to help researchers for designing diagnostic test studies and calculating sample size in studies evaluating test performance. For complex studies clinicians are encouraged to consult a statistician to help in the design and analysis for an accurate determination of the sample size.

• Journal of Ocean Engineering and Technology
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• v.24 no.1
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• pp.166-171
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• 2010

In this paper, the front-end of a digital receiver with a 25 kHz carrier frequency, 5 kHz symbol rate, and any excess-bandwidth is designed using two basic facts. The first is known as the uniform sampling theorem, which states that the sampled sequence might not suffer from aliasing even if its sampling rate is lower than the Nyquist sampling rate if the analog signal is a bandpass one. The other fact is that if the sampling rate is 4 times the center frequency of the sampled sequence, the front-end processing complexity can be dramatically reduced due to the half of the sampled sequence to be multiplied by zero in the demixing process. Furthermore, the designed front-end is simplified by introducing sub-filters and sub-sampling sequences. The designed front-end is composed of an A/D converter, which takes samples of a bandpass filtered signal at a 20 kHz rate; a serial-to-parallel converter, which converts a sampled bandpass sequence to 4 parallel sub-sample sequences; 4 sub-filter blocks, which act as a frequency shifter and lowpass filter for a complex sequence; 4 synchronized switches; and 2 adders. The designed front-end dramatically reduces the computational complexity by more than 50% for frequency shifting and lowpass filtering operations since a conventional front-end requires a frequency shifting and two lowpass filtering operations to get one lowpass complex sample, while the proposed front-end requires only four filtering operation to get four lowpass complex samples, which is equivalent to one filtering operation for one sample.

• Transactions of Materials Processing
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• v.7 no.3
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• pp.225-232
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• 1998

This article is aimed primarily at establishing a process planning method for complex circular shells. For the deep drawing of complex shaped shell, the optimum process design is required to reduce the trial cost improve the quality, increase the productivity and shorten the delivery. The present approach which is related to the optimum process planning is based on the empirical knowledge through trial and error in the industrial field. In order to check the validity and the effectiveness of proposed work a sample process design has been applied to the multi-stepped deep drawing of com-plex shell considering the process variables such as drawing rate radius and blank development. In particular the difference between the limiting drawing rate and to optimum drawing rate has been discussed and the usefulness of present suggestion has been shown.

• Journal of Integrative Natural Science
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• v.5 no.3
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• pp.157-162
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• 2012

Measurement error is one of main source of error in survey. It is generally defined as the difference between an observed value and an underlying true value. An observed value with error may be expressed as a function of the true value plus error term. In some cases, the measurement error variance may be also a function of the unknown true value. The error variance function can be rewritten as a function of true value multiplied by a scale factor. This research explore methods for estimation of the measurement error variance based on the data from complex sampling design. We consider the case in which the variance of mesurement error is a linear function of unknown true value, and the error variance scale factor is small. We applied our results to the U.S. Third National Health and Nutrition Examination Survey (the U.S. NHANES III) data for empirical analyses, which has replicate measurements for relatively small subset of initial respondents's group.

• Journal of Preventive Medicine and Public Health
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• v.46 no.2
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• pp.96-104
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• 2013

Objectives: The inherent nature of the Korean National Health and Nutrition Examination Survey (KNHANES) design requires special analysis by incorporating sample weights, stratification, and clustering not used in ordinary statistical procedures. Methods: This study investigated the proportion of research papers that have used an appropriate statistical methodology out of the research papers analyzing the KNHANES cited in the PubMed online system from 2007 to 2012. We also compared differences in mean and regression estimates between the ordinary statistical data analyses without sampling weight and design-based data analyses using the KNHANES 2008 to 2010. Results: Of the 247 research articles cited in PubMed, only 19.8% of all articles used survey design analysis, compared with 80.2% of articles that used ordinary statistical analysis, treating KNHANES data as if it were collected using a simple random sampling method. Means and standard errors differed between the ordinary statistical data analyses and design-based analyses, and the standard errors in the design-based analyses tended to be larger than those in the ordinary statistical data analyses. Conclusions: Ignoring complex survey design can result in biased estimates and overstated significance levels. Sample weights, stratification, and clustering of the design must be incorporated into analyses to ensure the development of appropriate estimates and standard errors of these estimates.