• Communications for Statistical Applications and Methods
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• 제22권3호
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• pp.209-222
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• 2015

Time series are used in many studies for model building and analysis. We must be very careful to understand the kind of time series data used in the analysis. In this review article, we will begin with some issues related to the use of aggregate and systematic sampling time series. Since several time series are often used in a study of the relationship of variables, we will also consider vector time series modeling and analysis. Although the basic procedures of model building between univariate time series and vector time series are the same, there are some important phenomena which are unique to vector time series. Therefore, we will also discuss some issues related to vector time models. Understanding these issues is important when we use time series data in modeling and analysis, regardless of whether it is a univariate or multivariate time series.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집B
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• pp.404-409
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• 2000

Growth characteristics of silica particles have been studied experimentally using in situ sampling technique from $H_2/O_2TEOS$ diffusion flame with carefully devised sampling probe. Verification of sampling result was done through new method and effects of flame condition and TEOS flow rate on growth characteristics of silica particles were investigated. By comparing particles sampled by thermophoretic sampling in flame with those by collector sampling after probe, particles do not change before and after probe sampling, which was clearly proved from the fact that the result of TEM image analysis makes good agreement with that of SMPS measurement. As flame temperature increases, the effect of coalescence or sintering becomes important mechanism during growth of silica particles, resulting in canceling the effect of coagulation, which makes mean diameter of silica particles increase slowly. With increase in TEOS flow rate, the number concentration of generated silica particle increases but residence time of particles in flame decreases. As a result, there exists upper limit to which the diameter of silica particle increases under same flame condition.

• Journal of the korean society of oceanography
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• 제34권4호
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• pp.200-206
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• 1999

Seawater sampling is the primary task for the study of the marine environmental parameters that require shipboard or laboratory experiments for their analyses, and is also required for the calibration of some instruments for in situ measurement. A new automatic bottle (AUTTLE) is developed for seawater sampling at any desired time and water depth by self-triggering. Both any type of single or assembled mooring for 15 days and manual actuation by using a remote messenger as existing instantaneous single point water samplers are possible. Its sampling capacity and the resolution of time setting are 2 liters and 1 second, respectively. The result of a field experiment with an optical backscattering sensor (OBS) and a total of 14 AUTTLES for the in situ calibration of the OBS shows that the AUTTLE must improve our understanding on the behavior of the sand/mud mixtures in the environments with high waves and strong tides. The AUTTLE will serve as a valuable instrument in the various fields of oceanography, especially where synchronized seawater sampling at several sites is required and/or the information in storm period is important.

• Smart Structures and Systems
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• 제17권4호
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• pp.611-629
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• 2016

This study presents a new approach of surrogate modeling for time-consuming finite element analysis. A surrogate model is widely used to reduce the computational cost under an iterative computational analysis. Although a variety of the methods have been widely investigated, there are still difficulties in surrogate modeling from a practical point of view: (1) How to derive optimal design of experiments (i.e., the number of training samples and their locations); and (2) diagnostics of the surrogate model. To overcome these difficulties, we propose a sequential surrogate modeling based on Gaussian process model (GPM) with self-adaptive sampling. The proposed approach not only enables further sampling to make GPM more accurate, but also evaluates the model adequacy within a sequential framework. The applicability of the proposed approach is first demonstrated by using mathematical test functions. Then, it is applied as a substitute of the iterative finite element analysis to Monte Carlo simulation for a response uncertainty analysis under correlated input uncertainties. In all numerical studies, it is successful to build GPM automatically with the minimal user intervention. The proposed approach can be customized for the various response surfaces and help a less experienced user save his/her efforts.

• Bulletin of the Korean Chemical Society
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• 제34권8호
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• pp.2353-2357
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• 2013

The objective of this study was to develop a simple, less time-consuming and accurate sampling technique based on solid-phase sorption with activated carbon as the sorbents. The results from solid-phase sorption techniques were compared to that from a conventional solvent impinger-based technique to confirm the efficacy of the proposed method. The laboratory results indicated that the solid-phase sorption method was suitable for the determination of siloxanes as the measured concentrations were similar to that from a solvent impinge method. The data from solid-phase sorption method showed excellent recovery and reproducibility while the sampling was less labor intensive and less time consuming than the solvent impinge method. Following the laboratory tests, the solid-phase sorption technique was successfully applied to sampling biogas from a field site. This study shows that the activated carbon-based solid-phase sorption can be a reliable and less time-consuming option for the sampling and collection of siloxanes under various different landfill conditions.

• Structural Engineering and Mechanics
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• 제84권3호
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• pp.323-335
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• 2022

The main idea of the framework is to seamlessly combine a reasonably accurate and fast surrogate model with the importance sampling strategy. Developing a surrogate model for predicting structures' dynamic responses is challenging because it involves high-dimensional inputs and outputs. For this purpose, a novel surrogate model based on cutting-edge deep learning architectures specialized for capturing temporal relationships within time-series data, namely Long-Short term memory layer and Transformer layer, is designed. After being properly trained, the surrogate model could be utilized in place of the finite element method to evaluate structures' responses without requiring any specialized software. On the other hand, the importance sampling is adopted to reduce the number of calculations required when computing the failure probability by drawing more relevant samples near critical areas. Thanks to the portability of the trained surrogate model, one can integrate the latter with the Importance sampling in a straightforward fashion, forming an efficient framework called TTIS, which represents double advantages: less number of calculations is needed, and the computational time of each calculation is significantly reduced. The proposed approach's applicability and efficiency are demonstrated through three examples with increasing complexity, involving a 1D beam, a 2D frame, and a 3D building structure. The results show that compared to the conventional Monte Carlo simulation, the proposed method can provide highly similar reliability results with a reduction of up to four orders of magnitudes in time complexity.

• 한국정밀공학회지
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• 제31권11호
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• pp.999-1006
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• 2014

In this investigation, we explain the sub-sampling technique of white light scanning interferometry (WLSI) to improve the measurement speed. In addition to the previous work using Fourier domain analysis, several methods to extract the height from the correlogram of WLSI are described with the sub-sampling technique. Especially, Fourier-inverse Fourier transformation method adopting sub-sampling technique is proposed and the phase compensation technique is verified with simulation and experiments. The main advantage of sub-sampling is to speed up the measurements of WLSI but the precision such as repeatability is slightly poor. In case of measuring the sample which has high height step or difference, the proposed technique can be widely used to reduce the measurement time.

• 산업경영시스템학회지
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• 제34권2호
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• pp.1-8
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• 2011

This paper proposes a variable sampling interval multivariate $T^2$ control chart with sampling at fixed times, where samples are taken at specified equally spaced fixed time points and additional samples are allowed between these fixed times when indicated by the preceding $T^2$ statistics. At fixed sampling points, the $T^2$ statistics are composed of all quality characteristics and a part of quality characteristics are selected to obtain $T^2$ statistics at additional sampling points. A Markov chain approach is used to evaluate the performance of the proposed chart. Numerical studies for the performance of the proposed chart show that the proposed chart reduces the observations obtained from a process and detects the assignable cause of a process with low correlated quality characteristics quickly.

• 대한전기학회논문지:전기기기및에너지변환시스템부문B
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• 제48권9호
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• pp.517-522
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• 1999

This paper addresses the issue of current sampling in a high performance AC drive system fed by a discontinuous PWM inverter. The effect of the sampling error due to the measurement delay produced by an input stage low pass filter and an A/D converter is described in the case of discontinuous PWM. To compensate for the sampling error, a method to estimate the delay time of the whole measurement system based on the measured current is proposed and its effectiveness is verified by experimental results. The proposed algorithm can automatically estimate the system delay introduced by the low pass filter and the A/D converter at the commissioning stage. By delaying the current sampling by the estimated value, experimental results indicate that more than 50% reduction of current ripple can be achieved.

• 대한의용생체공학회:의공학회지
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• 제27권1호
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• pp.6-13
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• 2006

Ultrasound visualization is a typical diagnosis method to examine organs, soft tissues and fetus data. It is difficult to visualize ultrasound data because the quality of the data might be degraded by artifact and speckle noise, and gathered with non-linear sampling. Rendering speed is too slow since we can not use additional data structures or procedures in rendering stage. In this paper, we use several visualization methods for fast rendering of ultrasound data. First method, denoted as adaptive ray sampling, is to reduce the number of samples by adjusting sampling interval in empty space. Secondly, we use early ray termination scheme with sufficiently wide sampling interval and low threshold value of opacity during color compositing. Lastly, we use bilinear interpolation instead of trilinear interpolation for sampling in transparent region. We conclude that our method reduces the rendering time without loss of image quality in comparison to the conventional methods.