• Advances in nano research
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• v.16 no.2
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• pp.187-200
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• 2024

This study focuses on wave propagation analysis in the curved nanobeam exposed to different thermal loadings based on the Nonlocal Strain Gradient Theory (NSGT). Mechanical properties of the constitutive materials are assumed to be temperature-dependent and functionally graded. For modeling, the governing equations are derived using Hamilton's principle. Using the proposed model, the effects of small-scale, geometrical, and thermo-mechanical parameters on the dynamic behavior of the curved nanobeam are studied. A small-scale parameter, Z, is taken into account that collectively represents the strain gradient and the nonlocal parameters. When Z<1 or Z>1, the phase velocity decreases/increases, and the stiffness-softening/hardening phenomenon occurs in the curved nanobeam. Accordingly, the phase velocity depends more on the strain gradient parameter rather than the nonlocal parameter. As the arc angle increases, more variations in the phase velocity emerge in small wavenumbers. Furthermore, an increase of ∆T causes a decrease in the phase velocity, mostly in the case of uniform temperature rise rather than heat conduction. For verification, the results are compared with those available for the straight nanobeam in the previous studies. It is believed that the findings will be helpful for different applications of curved nanostructures used in nano-devices.

• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.1989-2001
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• 2024

Artificial intelligence (AI) techniques are now being considered in the nuclear field, but application faces with the lack of actual plant data. For this reason, most previous studies on AI applications in nuclear power plants (NPPs) have relied on simulators or thermal-hydraulic codes to mimic the plants. However, it remains uncertain whether an AI model trained using a simulator can properly work in an actual NPP. To address this issue, this study suggests the use of metadata, which can give information about parameter trends. Referred to here as robust AI, this concept started with the idea that although the absolute value of a plant parameter differs between a simulator and actual NPP, the parameter trend is identical under the same scenario. Based on the proposed robust AI, this study designs an event diagnosis algorithm to classify abnormal and emergency scenarios in NPPs using prototypical learning. The algorithm was trained using a simulator referencing a Westinghouse 990 MWe reactor and then tested in different environments in Advanced Power Reactor 1400 MWe simulators. The algorithm demonstrated robustness with 100 % diagnostic accuracy (117 out of 117 scenarios). This indicates the potential of the robust AI-based algorithm to be used in actual plants.

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.954-959
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• 2008

This paper is concerned with the reliable $H_{\infty}$ controller design problem for uncertain linear systems against actuator failures. In the design, the $H_{\infty}$ performance of the closed-loop system is optimized during normal operation(without failures) while the system satisfies a prescribed $H_{\infty}$ performance level in the case of actuator failures. Single and parameter-dependent Lyapunov function approaches are applied in designing suboptimal reliable $H_{\infty}$ controllers. Simulation studies are presented to demonstrate the effectiveness of the proposed design procedures.

• Transactions on Electrical and Electronic Materials
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• v.13 no.5
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• pp.221-224
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• 2012

The present paper reports the comparative optical behavior of a pure nematic mixture E-24 and its anthraquinone dye doped sample. The variation in the ordinary and extraordinary refractive index ($n_o$, $n_e$) of the pure and dye doped samples with temperature has been discussed and it has been found that doped sample have a less refractive index compared to the pure sample. The variation in the order parameter for pure and doped samples with temperature has been discussed and it has been seen that the doped sample has a higher order parameter; the possible reasons have been discussed. The variations in birefringence and optical transmittance have also been presented here.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1181-1188
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• 2004

This paper reviews the main aspects of cardiovascular system dynamics with emphasis on modeling hemodynamic characteristics using a lumped parameter approach. Methodological and physiological aspects of the circulation dynamics are summarized with the help of existing mathematical models: The main characteristics of the hemodynamic elements, such as the heart and arterial and venous systems, are first described. Lumped models of micro-circulation and pulmonary circulation are introduced. We also discuss the feedback control of cardiovascular system. The control pathways that participate in feedback mechanisms (baroreceptors and cardiopulmonary receptors) are described to explain the interaction between hemodynamics and autonomic nerve control in the circulation. Based on a set-point model, the computational aspects of reflex control are explained. In final chapter we present the present research trend in this field and discuss the future studies of cardiovascular system modeling.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.172-175
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• 2002

This paper presents perceptual model with a stochastic rnultiresolution characteristic that can be applied with watermark embedding in the biorthogonal wavelet domain. The perceptual model with adaptive watermarking algorithm embed at the texture and edge region for more strongly embedded watermark by the SSQ(successive subband quantization). The watermark embedding is based on the computation of a NVF(noise visibility function) that have local image properties. This method uses non-stationary Gaussian model stationary Generalized Gaussian model because watermark has noise properties. In order to determine the optimal NVF, we consider the watermark as noise. The particularities of embedding in the stationary GG model use shape parameter and variance of each subband regions in multiresolution. To estimate the shape parameter, we use a moment matching method. Non-stationary Gaussian model use the local mean and variance of each subband. The experiment results of simulation were found to be excellent invisibility and robustness. Experiments of such distortion are executed by Stirmark benchmark test.

• Journal of Korean Academy of Nursing
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• v.29 no.5
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• pp.1030-1041
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• 1999

This study examined those problems noticed under the Asymptotically Generalized Least Squares estimator in evaluating a structural model of physical health. The problems were highly correlated parameter estimates and high standard errors of some parameter estimates. Separate analyses of the endogenous part of the model and of the metric of a latent factor revealed a highly skewed and kurtotic measurement indicator as the focal point of the manifested problems. Since the sample sizes are far below that needed to produce adequate AGLS estimates in the given modeling conditions, the adequacy of the Maximum Likelihood estimator is further examined with the robust statistics and the bootstrap method. These methods demonstrated that the ML methods were unbiased and statistical decisions based upon the ML standard errors remained almost the same. Suggestions are made for future studies adopting structural equation modeling technique in terms of selecting of a reference indicator and adopting those statistics corrected for nonormality.

• IE interfaces
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• v.15 no.2
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• pp.189-198
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• 2002

Simulated Annealing(SA) approach has been successfully applied to the combinatorial optimization problems with NP-hard complexity. To apply an SA algorithm to specific problems, generic parameters as well as problem-specific parameters must be determined. To overcome the embedded nature of SA, long computational time, some studies suggested the parameter design methods of determining SA related parameters. In this study, we propose a new parameter design approach based on robust design method. To show the effectiveness of the proposed method, the extensive computation experiments are conducted on the mixed-model sequencing problems.

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.325-335
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• 2003

Robust design is to identify appropriate settings of control factors that make the system's performance robust to to changes in the noise factors that represent the source of variation. In the Taguchi parameter design, the product array approach using orthogonal arrays is mainly used. However, it often requires an excessive number of experiments. An alternative approach, which is called the combined array approach, was suggested by Welch et. al. (1990) and studied by others. In these studies, only single response variable was considered. We propose how to simultaneously optimize multiple responses when we use the combined array approach.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.916-921
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• 2004

The penalty method has been widely applied to analyses of incompressible fluid flow. However, we have not yet found any prior studies that employed penalty method to analyze compressible fluid flow. In this study, with an eye on the apparent similarity between the slight compressible formulation and the penalty formulation, we have proposed a new approximate approach that can analyze compressible packing process using the penalty parameter l. Based on the assumption of the isothermal flow, a set of reference solutions was obtained to verify the validity of the proposed scheme. Furthermore, we have applied the proposed scheme to the analysis of the packing process of different cases.