• Language and Information
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• v.18 no.1
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• pp.53-75
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• 2014

This study discovers the dynamic nature of an interactional hierarchy as well as an institutional hierarchy in the use of Korean honorifics. Data was collected from the conversations of two Korean female interlocutors. The interlocutors met for the first time in the U.S. and often changed their use of honorifics. The paper examines the method in which the two interlocutors negotiate hierarchies during interaction and how the negotiation is reflected in their use of honorific shifts. The paper also investigates honorific shifts in terms of self-representation to suggest that there is another hierarchy at work other than the institutional hierarchy. An examination of the data shows that the shifts occurred not randomly but strategically. The findings suggest that 1) interlocutors may negotiate interactional hierarchy during their conversation, often in the same sentence, 2) interactional hierarchy often cross the boundary of the institutional hierarchy to obtain interactional goals, in this case, intimacy, and 3) the utterance contents may play a significant role in the interlocutors' honorific shifts.

• The Korean Journal of Applied Statistics
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• v.22 no.6
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• pp.1191-1201
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• 2009

The cumulative sum(CUSUM) control charts are typically used for detecting small level shifts in process control. To control an auto-correlated process, the model-based control methods can be employed, in which the residuals from fitting a time series model are applied to the CUSUM chart. However, the persistent level shifts in the original process may lead to varying mean shifts in residuals, which may deteriorate detection performance significantly. Therefore, in this paper, focussing on ARMA(1,1), we propose a new CUSUM type control method which can detect the dynamic mean shifts in residuals especially with oscillating pattern effectively and, through the simulation study, evaluate its performance by comparing with other various CUSUM type control methods introduced so far.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.12
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• pp.60-69
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• 1997

We present an average method based on the multirate signal processing and dynamic allocation average for the purpose of monitoring event-related potentials(ERP) and continuously and dynamically. In the proposed method, first, latency shifts are detected through the cross correlation between a current response and the reference response. Then, the multirate signal processing which is composed of up-sampler, lowpass filter, and down sampler is performed to compensate the latency shifts of the reference response, therefore we obtain the reference response with a peak latencies compenated by those of a current response. Finally, the single response is obtained by averaging the compensated reference response and a current response. In the simulation, the results of quantitative evaluation by simulation and the results using linical data are presented. From the result, the proposed method reflects dynamic time-varying ERP more exactly than previous methods and is also effective in consecutive monitoring of ERP.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.282-287
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• 2007

Humanoid and android robots are emerging as a trend shifts from industrial robot to personal robot. So human-robot interaction will increase. Ultimate objective of humanoid and android would be a robot like a human. In this aspect, implementation of robot's facial expression is necessary in making a human-like robot. This paper proposes a dynamic emotion model for a mascot-type robot to display similar facial and more recognizable expressions.

• Korean Journal of Child Studies
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• v.29 no.1
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• pp.275-292
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• 2008

This study investigated the effects of a teaching process using dynamic assessment for a unit on young children's measurement ability. Subjects were 45 5-year-old children in a kindergarten in Busan. The instrument was the Dynamic Assessment Tools for Young Children's Measurement Ability (Hwang & Ko, 2(07). Assessment consisted of four steps: pre-test, learning, transfer, post-test. Results were that at post-test, there were significant differences in scores of measurement ability between the dynamic assessment and control groups. In the dynamic assessment group there was significant improvement in length, width and weight between pre- and post-tests and there were significant shifts of measurement strategies and measurement errors between the pre- and post-tests.

• Journal of Photoscience
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• v.9 no.2
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• pp.110-113
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• 2002

We demonstrate here a dynamic structure of bacteriorhodopsin (bR) as revealed by $^{13}$ C NMR studies on [3_$^{13}$ C]_,[1-$^{13}$ C]Ala- and/or Val-labeled wild type and a variety of site-directed mutants at ambient temperature. For this purpose, well-resolved (up to twelve) I$^{13}$ C NMR peaks were assigned with reference to the displacement of peaks due to the conformation-dependent I$^{13}$ C chemical shifts and reduced peak-intensities due to site-directed mutations. Revealed bR structure was not rigid as anticipated from 2D crystals of hexagonal array but a dynamically heterogeneous, undergoing a variety of local fluctuations depending upon specific site with frequency range of 10$^2$ -10$^{8}$ Hz. In particular, dynamics- dependent suppression of peaks turned out to be very sensitive to the motion of 10$^{-4}$ s and 10$^{-5}$ s interfered with frequency of magic angle spinning and proton decoupling, respectively. It is also noteworthy that such dynamic feature is strongly dependent upon the manner of 2D crystalline packing: $^{13}$ C NMR peaks of monomeric bR yielded either highly broadened or completely suppressed signals, depending upon the type of $^{13}$ C-labeled amino-acid residues.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.88-93
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• 2020

Based on the capture-emission energy (CEE) maps of CMOS devices, a physics-informed machine learning model for the bias temperature instability (BTI)-induced threshold voltage shifts and low frequency noise is presented. In order to incorporate physics theories into the machine learning model, the integration of artificial neural network (IANN) is employed for the computation of the threshold voltage shifts and low frequency noise. The model combines the computational efficiency of IANN with the optimal estimation of Gaussian mixture model (GMM) with soft clustering. It enables full lifetime prediction of BTI under various stress and recovery conditions and provides accurate prediction of the dynamic behavior of the original measured data.

• Smart Structures and Systems
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• v.15 no.2
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• pp.375-393
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• 2015

In this study, local dynamic characteristics of mountable PZT interfaces are numerically analyzed to verify their feasibility on impedance monitoring of the prestress-loss in tendon anchorage subsystems. Firstly, a prestressed tendon-anchorage system with mountable PZT interfaces is described. Two types of mountable interfaces which are different in geometric and boundary conditions are designed for impedance monitoring in the tendon-anchorage subsystems. Secondly, laboratory experiments are performed to evaluate the impedance monitoring via the two mountable PZT interfaces placed on the tendon-anchorage under the variation of prestress forces. Impedance features such as frequency-shifts and root-mean-square-deviations are quantified for the two PZT interfaces. Finally, local dynamic characteristics of the two PZT interfaces are numerically analyzed to verify their performances on impedance monitoring at the tendon-anchorage system. For the two PZT interfaces, the relationships between structural parameters and local vibration responses are examined by modal sensitivity analyses.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.81-87
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• 2000

This paper presents an application of forced oscillation technique to measure pitch dynamic stability derivatives of a missile model in the low speed wind tunnel. The missile model is oscillated by D.C. electric servomotor with constant amplitudes and frequencies. Phase shift is determined as the difference of peak values between input and output signals from the dynamic stability balance installed at the center of gravity of the model. Stability derivatives were calculated by using phase shifts, amplitudes, forcing moments and input frequencies. Test results show the proper usage of the force oscillation technique with good damping effects.

• International Journal of Control, Automation, and Systems
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• v.6 no.1
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• pp.109-118
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• 2008

We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.