• Korean Journal of Fisheries and Aquatic Sciences
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• v.50 no.5
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• pp.594-604
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• 2017

The Korean National Institute of Fisheries Science (NIFS) has biannually (spring and fall, respectively) deployed a bottom trawl survey along the coastal areas for last decade, taking samples on a regular basis (i.e., a systematic sampling). Despite the availability of the survey data, NIFS has not yet officially reported the estimates of the groundfish population sizes as well as has not evaluated uncertainty of the estimates. The objectives of our study were to infer the relative size of a fish population, applying two different sampling techniques (namely simple and stratified sampling) with different observation units to the NIFS survey data, and to compare those two techniques in bias and precision. For demonstration purposes, we used data on Pacific cod (Gadus macrocephalus) collected by the 2011-2015 surveys, and the results of simple and stratified sampling showed that the point estimates and precision varied by observation unit as well as the sampling technique.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.357-371
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• 2014

There are many studies related to imbalanced data in which the class distribution is highly skewed. To address the problem of imbalanced data, previous studies deal with resampling techniques which correct the skewness of the class distribution in each sampled subset by using under-sampling, over-sampling or hybrid-sampling such as SMOTE. Ensemble methods have also alleviated the problem of class imbalanced data. In this paper, we compare around a dozen algorithms that combine the ensemble methods and resampling techniques based on simulated data sets generated by the Backbone model, which can handle the imbalance rate. The results on various real imbalanced data sets are also presented to compare the effectiveness of algorithms. As a result, we highly recommend the resampling technique combining ensemble methods for imbalanced data in which the proportion of the minority class is less than 10%. We also find that each ensemble method has a well-matched sampling technique. The algorithms which combine bagging or random forest ensembles with random undersampling tend to perform well; however, the boosting ensemble appears to perform better with over-sampling. All ensemble methods combined with SMOTE outperform in most situations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.233-239
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• 2022

The injection molding process is a process in which thermoplastic resin is heated and made into a fluid state, injected under pressure into the cavity of a mold, and then cooled in the mold to produce a product identical to the shape of the cavity of the mold. It is a process that enables mass production and complex shapes, and various factors such as resin temperature, mold temperature, injection speed, and pressure affect product quality. In the data collected at the manufacturing site, there is a lot of data related to good products, but there is little data related to defective products, resulting in serious data imbalance. In order to efficiently solve this data imbalance, undersampling, oversampling, and composite sampling are usally applied. In this study, oversampling techniques such as random oversampling (ROS), minority class oversampling (SMOTE), ADASYN(Adaptive Synthetic Sampling), etc., which amplify data of the minority class by the majority class, and complex sampling using both undersampling and oversampling, are applied. For composite sampling, SMOTE+ENN and SMOTE+Tomek were used. Artificial neural network techniques is used to predict product quality. Especially, MLP and RNN are applied as artificial neural network techniques, and optimization of various parameters for MLP and RNN is required. In this study, we proposed an SA technique that optimizes the choice of the sampling method, the ratio of minority classes for sampling method, the batch size and the number of hidden layer units for parameters of MLP and RNN. The existing sampling methods and the proposed SA method were compared using accuracy, precision, recall, and F1 Score to prove the superiority of the proposed method.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.158-167
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• 1992

This paper represents the new techniques for optimal sampling plans of reliability applying the mathematical complex number(real and imaginary number) in the complex system of reliability. The research formulation represent a mathematical model Which preserves all essential aspects of the main and auxiliary factors of the research objectives. It is important to formule the problem in good agreement with the objective of the research considering the main and auxilary factors which affect the system performance. This model was repeatedly tested to determine the required statistical chatacteristics which in themselves determine the actual and standard distributions. The evaluation programs and techniques are developed for establishing criteria for sampling plans of reliability effectiveness, and the evaluation of system performance was based on the complex stochastic process(derived by the Runge-Kutta method. by kolmogorv's criterion and the transform of a solution to a Sturon-Liouville equation.) The special structure of this mathematical model is exploited to develop the optimal sampling plans of reliability in the complex system.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.227-237
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• 2004

In this paper we presented a Bayesian inference approach for estimating the location and scale parameters of the lognormal distribution using iterative Gibbs sampling algorithm. We also presented estimation of location parameter by two non iterative methods, importance sampling and weighted bootstrap assuming scale parameter as known. The estimates by non iterative techniques do not depend on the specification of hyper parameters which is optimal from the Bayesian point of view. The estimates obtained by more sophisticated Gibbs sampler vary slightly with the choices of hyper parameters. The objective of this paper is to illustrate these tools in a simpler setup which may be essential in more complicated situations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.11a
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• pp.35-36
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• 2008

• 전기의세계
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• v.25 no.6
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• pp.89-96
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• 1976

In this paper we deal with that the performance indices by the three adaptive sampling control laws are computed and compared. It shows that the most effective control law is the integral input difference method. The techniques of simulation by Analog/Hybrid computer are presented and the results of the output illustrate that the maximum and minimum sampling interval can be applied to the time sharing of digital controller or computer.

• Journal of Korean Society for Quality Management
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• v.40 no.3
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• pp.245-258
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• 2012

Purpose: Recently, many quality issues are aroused in military forces, such as failures in K-series weapons, combat boots defects and 40mm ammunition explosion accident. To address these problems, the one and only government defense quality assurance agency, DTaQ(Defense Agency for Technology & Quality) tried to improve many quality assurance procedures and introduced new systems such as MRA(Manufacturing Readiness Assessment), TRA(Technology Readiness Assessment), and etc. However, as the amount of war supplies increasing every year, the resource(budget and manpower) for quality assurance is limited. Therefore, DTaQ had difficulty to handle the issue efficiently and effectively, and we propose the method to address this problem. Methods: The most popular quality assurance technique is a sampling method, in this research, we first review the many sampling techniques and compare the strength and weakness of each method. After then, we selected the most appropriate sampling techniques and applied the procedures in combat force support material and ammunition areas. Results: We can reduce the number of samples dramatically, thus the required amount of labor time and money can be saved. Also, the new sampling technique enforces the supplier to produce the product which meets the target value(desirable value). Conclusion: We can reduce the number of samples dramatically, thus the required amount of labor time and money can be saved. Also, the new sampling technique enforces the supplier to produce the product which meets the target value(desirable value). Lastly, since the new sampling method requires many numerical calculations, we developed a simple android OS smart-phone application which can be used easily in field.

• Journal of Korea Entertainment Industry Association
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• v.13 no.7
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• pp.205-218
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• 2019

Music sampling, which has been popular since hip-hop DJs used it in the 1970s, is now one of methods of producing music that is used regardless of genre or country. In this study, an overall production methodology for music sampling was presented through in terms of content and techniques. First of all, in terms of the contents, we classified them into the reuse and length of materials, and the function of samples in the mixed songs. In terms of the techniques, editing and effecting techniques were classified. By combining these elements, the methodology of music sampling applicable to the productions as well as the analysis was presented. Based on this methodology, the sampled songs of Korean Popular musicians - Jang Ki-ha and Faces, Epik High, The Quiet, and DJ DOC - were successfully analysed. Through the analysis process, the organic relationship of elements within the methodology was investigated, and the results of the analysis showed the effectiveness of the proposed methodology. This study can be meaningful in laying the groundwork for applying music sampling directly when actually producing songs or analyzing sampled songs.

• Proceedings of the Korean Geotechical Society Conference
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• 1999.10a
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• pp.95-102
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• 1999

It is important to estimate the magnitude of settlement and the time of primary consolidation in geotechnical engineering projects. For these purposes, site explorations and laboratory tests are usually performed. However, the mechanical properties determined from laboratory tests on the samples obtained by different sampling techniques show different trends. In this study, three types of consolidation test were carried out on the soil samples obtained by three different sampling techniques (76mm tube, 76mm piston, and block samples), to verify the effect of sample disturbance on consolidation properties. It was found that sampling methods have influence on the $\varepsilon$ - log $\sigma$'$_{v}$ relationship. While insignificant difference of compression indices from the samples obtained by different sampling techniques was observed in compression region, these values showed a different trend in precompression region. The values of $c_{v}$ and k of block samples had a tendency to be larger than those of piston and tube samples. At consolidation pressure larger than $\sigma$'$_{p}$, however, these properties became similar regardless of sampling methods. The block and piston samples gave slightly higher values of $C_{a/}$ $C_{c}$ than tube samples. In the results of I $L_{EOP}$ and CRS test, it was observed that the values of $\sigma$'$_{p measured}$/$\sigma$'$_{p best estimated}$ of Yang-San clay decreases when strain becomes larger than 1.0% and that precompression strain of block samples is in the range of 1.5~2.0% while those of piston and tube samples are 1.75~3.75%. It was also shown that the values of $\sigma$'$_{p}$ of block samples exceed those of piston and tube samples by about 6~10%.6~10%.%.%.%.%.