• The Journal of the Acoustical Society of Korea
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• v.14 no.2E
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• pp.19-24
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• 1995

The maximum entropy method is a well-known parametric estimation method of the power spectrum with high-resolution for short-time signals. Although a parametric estimation method for the bispectrum was proposed in recent years, it is not easy to estimate the bispectrum with high resolution for relatively short-time signals of which the total length is about 1000 data points. In this paper, a bispectrum estimation method is proposed to estimate the high-resolution bispectrum even for the relatively short-time signals.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.171-178
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• 2010

Resonant parametric perturbation (RPP) method is an effective non-feedback method for controlling chaos. In this paper, the above method is applied for the current programmed buck-boost dc-dc converter which exhibits chaotic for wide parameter variations. The different possible operating regimes leading to chaotic operation of the current mode controlled buck-boost converter is discussed and the control of chaos by RPP method is demonstrated through computer simulations and experimental studies. The converter is stabilized to period 1 operation practically.

• Journal of the Society of Naval Architects of Korea
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• v.49 no.1
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• pp.60-67
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• 2012

This study considers the numerical analysis on parametric roll for container ships. As a method of numerical simulation, an impulse-response-function approach is applied in time domain. A systematic study is carried out for the parametric roll of two container ships, particularly observing the sensitivity of computational results to some parameters which can affect the analysis of parametric roll. The parameters to be considered are metacentric height (GM), simulation time window, and the discretization of wave spectrum. Based on the result of parametric roll simulation, numerical sensitivity and uncertainty in computational analysis are discussed.

• Journal of Advanced Marine Engineering and Technology
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• v.16 no.5
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• pp.67-76
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• 1992

This paper describes the vibration characteristic of second-order nonlinear systems subjected to parametric excitation. Emphasis is put on the examination of the hydrodynamic nonlinear damping effect on limiting the response amplitudes of parametric vibration. Since the parametric vibration is described by the Mathieu equation, the Mathieu stability chart is examined in this paper. In addition, the steady-state solutions of the nonlinear Mathieu equation in the first instability region are obtained by using a perturbation technique and are compared with those by a numerical integration method. It is shown that the response amplitudes of parametric vibration are limited even in unstable conditions by hydrodynamic nonlinear damping force. The largest reponse amplitude of parametric vibration occurs in the first instability region of Mathieu stability chart. The parametric excitation induces the response of a dynamic system to be subharmonic, superharmonic or chaotic according to their dynamic conditions.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.519-526
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• 2019

Response dimension reduction in a sufficient dimension reduction (SDR) context has been widely ignored until Yoo and Cook (Computational Statistics and Data Analysis, 53, 334-343, 2008) founded theories for it and developed an estimation approach. Recent research in SDR shows that a semi-parametric approach can outperform conventional non-parametric SDR methods. Yoo (Statistics: A Journal of Theoretical and Applied Statistics, 52, 409-425, 2018) developed a semi-parametric approach for response reduction in Yoo and Cook (2008) context, and Yoo (Journal of the Korean Statistical Society, 2019) completes the semi-parametric approach by proposing an unstructured method. This paper theoretically discusses and provides insightful remarks on three versions of semi-parametric approaches that can be useful for statistical practitioners. It is also possible to avoid numerical instability by presenting the results for an orthogonal transformation of the response variables.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.615-627
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• 2022

Principal Fitted Component (PFC) is a semi-parametric sufficient dimension reduction (SDR) method, which is originally proposed in Cook (2007). According to Cook (2007), the PFC has a connection with other usual non-parametric SDR methods. The connection is limited to sliced inverse regression (Li, 1991) and ordinary least squares. Since there is no direct comparison between the two approaches in various forward regressions up to date, a practical guidance between the two approaches is necessary for usual statistical practitioners. To fill this practical necessity, in this paper, we newly derive a connection of the PFC to covariance methods (Yin and Cook, 2002), which is one of the most popular SDR methods. Also, intensive numerical studies have done closely to examine and compare the estimation performances of the semi- and non-parametric SDR methods for various forward regressions. The founding from the numerical studies are confirmed in a real data example.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1504-1514
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• 2018

The objective of this study is to compare the suitability of a non-parametric and 3 parametric distributions in the characterization of prediction intervals of photovoltaic power forecasts with high confidence levels. The prediction intervals of the forecasts are calculated using a method based on recent past data similar to the target forecast input data, and on a distribution assumption for the forecast error. To compare the suitability of the distributions, prediction intervals were calculated using the proposed method and each of the 4 distributions. The calculations were done for one year of day-ahead forecasts of hourly power generation of 432 PV systems. The systems have different sizes and specifications, and are installed in different locations in Japan. The results show that, in general, the non-parametric distribution assumption for the forecast error yielded the best prediction intervals. For example, with a confidence level of 85% the use of the non-parametric distribution assumption yielded a median annual forecast error coverage of 86.9%. This result was close to the one obtained with the Laplacian distribution assumption (87.8% of coverage for the same confidence level). Contrasting with that, using a Gaussian and Hyperbolic distributions yielded median annual forecast error coverage of 89.5% and 90.5%.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.768-773
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• 2009

This paper demonstrates the digital communication in air using the parametric array. The stepped-plate transducer which is suitable for high-power and high-efficient radiation is used to generate the difference frequency wave with the parametric array. The primary frequencies are selected to 83 kHz and 122 kHz and the resulting difference frequency wave at the frequency of 39 kHz is used for the communication. The modulation method is selected to On-Off Keying method. The waveform and signal-to-noise ratio (SNR) is measured and analyzed to see the characteristics of the digital communication using the parametric array. The proper distance for the communication using parametric array is about 3 m. The measured beam width of the 3dB SNR reduction was $14^{\circ}$. The possibility of the communication in air using the parametric array is confirmed and the high directional characteristic of the communication using the parametric array is expected to have the advantages for the multi path and the security problems.

• The Journal of Society for e-Business Studies
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• v.9 no.4
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• pp.117-136
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• 2004

As the time-to-market gets more important for competitiveness of an enterprise in manufacturing industry, it becomes important to shorten the development cycle of a product. Reuse of existing design models and e-Catalog for components are required for faster product development. To achieve this goal, an electric catalog must provide parametric CAD models since parametric information is indispensable for configuration design. There are difficulties in building up a parametric library of all the necessary combination using a CAD system, since we have too many combinations of components for a product. For example, there are at least 80 million combinations of components on one page of paper catalog of a mold base. To solve this problem, we propose the method of table parametric for the automatic generation of parametric CAD models. Any combination of mold base can be generated by mapping between a classification system of an electric catalog and the design parameters set of the table parametric. We propose how to select parametric models and to construct the design parameters set.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.276-285
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• 1997

Engineers need to reduce the product design time interval and deal with frequent design changes. For this purpose a design expert system has been developed where a 3D CAD system is used for the visualization of a design layout especially the car audio design. This expert system is based on the configuration design methodology, one of the design methods which emulates the engineering design process, and the parametric design method. The design methods and heuristic knowledge are represented as rules, and design parts are represented as objects with properties. After an inference process, design parameters are extracted and they are used leer the parametric design. This study focused on the shape visualization of product components in the preliminary design phase.