• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.502-507
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• 2003

Toward the development of practical methods for observed data oriented bispectral estimation, an automatic means for determining the smoothing bandwidth of bispectral windows is proposed, that can also provide an associated optimum bispectral estimate of stationary non-Gaussian signals, systematically only from an observed time series datum of finite length. For the conventional non-parametric bispectral estimation, the MSE (mean squared error) of the normalized estimate is reviewed under a certain mixing condition and sufficient data length, mainly from the viewpoint of the inverse relation between its bias and variance with respect to the smoothing bandwidth. Based on the fundamental relation, a systematic method not only for determining the bandwidth, but also for obtaining the optimum bispectral estimate is presented by newly introducing a MSE evaluation index of the estimate only from an observed time series datum of finite length. The effectiveness and fundamental features of the proposed method are illustrated by the basic results of numerical experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.931-938
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• 2008

In this paper, a novel localization algorithm robust to the unmodeled systematic odometry errors is proposed for low-cost non-holonomic mobile robots. It is well known that the most pose estimators using odometry measurements cannot avoid the performance degradation due to the dead-reckoning of systematic odometry errors. As a remedy for this problem, we tty to reflect the wheelbase error in the robot motion model as a parametric uncertainty. Applying the Krein space estimation theory for the discrete-time uncertain nonlinear motion model results in the extended robust Kalman filter. This idea comes from the fact that systematic odometry errors might be regarded as the parametric uncertainties satisfying the sum quadratic constrains (SQCs). The advantage of the proposed methodology is that it has the same recursive structure as the conventional extended Kalman filter, which makes our scheme suitable for real-time applications. Moreover, it guarantees the satisfactoty localization performance even in the presence of wheelbase uncertainty which is hard to model or estimate but often arises from real driving environments. The computer simulations will be given to demonstrate the robustness of the suggested localization algorithm.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1908-1916
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• 2018

This paper proposes a controller design method for suppressing the resonance generated in the slave motor in the middle and low speed operation range, according to the load and parameter differences between two motors, during parallel operation using the master and slave method that controls two surface permanent magnet synchronous motors connected in parallel by a single inverter. The proposed resonance suppression controller is directly obtained by analyzing the resonance characteristics, using the lead controller method. Therefore, it is possible to fundamentally reduce trial and error to set the controller gain. In addition, because the proposed resonance suppression controller was designed as a lead controller, the stability region of the system increased owing to the added zero point, making the system robust with respect to parametric variations. Simulations and experiments confirmed the usefulness of the proposed method and the system's robustness with respect to parametric variations.

• Smart Structures and Systems
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• v.30 no.1
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• pp.35-47
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• 2022

Data-driven engineering is crucial for information delivery between design, fabrication, assembly, and maintenance of prefabricated structures. Design for manufacturing and assembly (DfMA) is a critical methodology for prefabricated bridge structures. In this study, a novel concept of digital engineering model that combined existing knowledge of DfMA with object-oriented parametric modeling technologies was developed. Three-dimensional (3D) geometry models and their data models for each phase of a construction project were defined for information delivery. Digital design models were used for conceptual design, including aesthetic consideration and possible variation during fabrication and assembly. The seismic performance of a bridge pier was evaluated by linking the design parameters to the calculated moment-curvature curves. Control parameters were selected to consider the tolerance control and revision of the digital models. Digitalized fabrication of the prefabricated members was realized using the digital fabrication model with G-code for a concrete printer or a robot. The fabrication error was evaluated and the design digital models were updated. The revised fabrication models were used in the preassembly simulation to guarantee constructability. For the maintenance of the bridge, the as-built information was defined for the prefabricated bridge piers. The results of this process revealed that data-driven information delivery is crucial for lifecycle management of prefabricated bridge piers.

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.347-356
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• 2022

This article is concerned with asymmetric volatility models for financial time series. A generalization of standard single-threshold volatility model is discussed via multiple-threshold in which we specialize to twothreshold case for ease of presentation. An empirical illustration is made by analyzing S&P500 data from NYSE (New York Stock Exchange). For comparison measures between competing models, parametric bootstrap method is used to generate forecast distributions from which summary statistics of CP (Coverage Probability) and PE (Prediction Error) are obtained. It is demonstrated that our suggestion is useful in the field of asymmetric volatility analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.4D
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• pp.595-601
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• 2011

There is currently applied to the unit cost per a distance (KRW/km) for estimating the conceptual cost of civil work on basic planning stage of high speed railroad. This unit cost is an arithmetic average value based on historical data, which could be in big error. It also is difficult to explain the deficiency comparing the estimated cost derived from next basic design stage. This study provides the conceptual estimation model using by the parametric method and regression analysis. Independent variables are the distance and the geological materials (earth, weathered rock, soft-rock, hard-rock), extracting from the actual data to 36 contracts. The deviation between the unit costs estimated using the developed model and the actual cost data is presented in the range from -0.4% to +31%. This range is acceptable compared the typical range "-30% to + 50%". This model will improve the accuracy of existing method and be expected to contribute to effective total cost management and the economic aspects, reduce the financial expenditure.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.3-9
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• 2012

In this paper, we present novel analysis results of sonar communication using parametric array. We consider transducer diameter, primary frequency, difference frequency and acoustic power as analysis parameters of communication performance. We calculate theoretical BER(Bit Error Rate) and channel capacity of MIMO(Multi Input and Multi Output) communication system. By considering practical parameters, we obtain optimum difference frequency generation condition. The obtained primary frequency is 560 kHz, difference frequency 45kHz and acoustic power is 28.05Watt. For BER of $10^{-4}$, the range gain of parametric array communication is 3.35km compared to primary frequency communication. For channel capacity of 10bps/Hz, the SISO and $2{\times}2$ MIMO communication range of parametric array communication are 3.8km and 3.98km respectively, while primary frequency communication range is 0.83km.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.3
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• pp.9-15
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• 2013

Recent works on ad hoc network study have shown that achievable throughput can be made to scale linearly with the number of receive antennas even if the transmitter has only a single antenna. In this paper, we propose a non-parametric linear minimum mean square error (MMSE) receiver for achieving further gain in performance when the channel state information at receiver (CSIR) of interferers is imperfect. The key feature to make our approach effective is to exploit the autocorrelation of the received signal. In fact, by incorporating the desired channel information on top of the observations including interference and noise only, the proposed method achieves large fraction of the optimal MMSE transmission capacity without transmission rate loss. From the SINR analysis as well as transmission capacity simulations in realistic ad hoc network system, we show that the proposed non-parametric linear MMSE receiver brings substantial performance gain over existing multiple receive antenna algorithms.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.245-253
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• 2011

Powers of rank transformed statistic for testing main effects and interaction effects for $2{\times}2$ factorial design in randomized complete block design are very superior to powers of parametric statistic without regard to the block size, composition method of effects and the type of population distributions such as exponential, double exponential, normal and uniform. $2{\times}2$ factorial design in RCBD increases error effects and decreases powers of parametric statistic which results in conservativeness. However powers of rank transformed statistic maintain relative preference. In general powers of rank transformed statistic show relative preference over those of parametric statistic with small block size and big effect size.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.6
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• pp.341-348
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• 2019

The purpose of this study is to model and analyze retractable large spatial structures by applying parametric modeling techniques. The modeling of wind loads in the analysis of typical structures including curved surfaces can be error-prone, and the processing time increases dramatically when there are many types of variables. However, the method based on StrAuto that was developed in previous research, facilitates the efficacious assignment of wind loads to structures and the rapid arrival of conclusions. As a result, it is possible to compare alternatives with various loads, including wind loads, to determine an optimal alternative much faster than the existing process. Further, it is almost impossible to directly input the wind load by calculating the area of an irregularly curved surface. However, the proposed method automatically assigns the wind load, which allows for automatic optimization in a structural analysis system. The approach was applied and optimized using several models, and the results are presented.