• Coupled systems mechanics
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• v.12 no.2
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• pp.183-197
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• 2023

Scarce research has been published on crack propagation fracture of flywheels manufactured with carbon fiber-reinforced polymers. The present work deals with a calculation method to determine the conditions for which a crack propagates in the axial direction of the flywheel. The assumptions are: flywheels made with just a single thick ply or ply clustering laminates, oriented following the hoop direction; a single crack is analyzed in the plane defined by the hoop and axial directions; the crack starts close to one of the free edges; its axial length is initially large enough so that its tip is far away from that free edge, and the crack expands the entire circumferential perimeter and keeps its concentric position. The developed method provides information for a good design of flywheels. It is concluded that a fracture-based crack propagation criterion generally occurs at a lower speed than a stress-based criterion. Also, that the evolution of failure with thickness using the fracture criterion is exponential, demonstrating that thin flywheels are relatively not sensitive to crack propagation, whereas thick ones are very prone.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2258-2263
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• 2003

This paper presents the design and development of an optimal fuzzy logic controller (FLC) for a laser tracking system. An optimal intelligent fuzzy logic controller was founded on integral criterion of the fuzzy models and three-dimensional fuzzy control. Research had been also concentrated on the methods for multivariable fuzzy models for the purposes of real-time process. Simulation results have shown remarkable tracking performance of this fuzzy PID controller.

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.237-250
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• 2002

Motivated by Cook's (1986) assessment of local influence by investigating the curvature of a surface associated with the overall discrepancy measure, this paper extends this idea to the linear regression model with AR(p) disturbances. Diagnostic for the linear regression models with AR(p) disturbances are discussed when simultaneous perturbations of the response vector are allowed. For the derived criterion, numerical studies demonstrate routine application of this work.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1047-1058
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• 2008

Prediction of total sales in information security industry is considered. Exponential smoothing and spline smoothing is applied to the time series of annual sales data. Due to the different survey items of every year, we recollect the original survey data by some basic criterion and predict the sales to 2014. We show the total sales in infonnation security industry are increasing gradually by year.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3128-3149
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• 2018

A number of effective methods for multiple-attribute group decision making (MAGDM) with interval-valued intuitionistic fuzzy numbers (IVIFNs) have been proposed in recent years. However, the different methods frequently yield different, even sometimes contradictory, results for the same problem. In this paper a novel criterion to determine the advantages and disadvantages of different methods is proposed. First, the decision-making process is divided into three parts: translation of experts' preferences, aggregation of experts' opinions, and comparison of the alternatives. Experts' preferences aggregation is considered the core step, and the quality of the collective matrix is considered the most important evaluation index for the aggregation methods. Then, methods to calculate the similarity measure, correlation, correlation coefficient, and energy of the intuitionistic fuzzy matrices are proposed, which are employed to evaluate the collective matrix. Thus, the optimal method can be selected by comparing the collective matrices when all the methods yield different results. Finally, a novel approach for aggregating experts' preferences with IVIFN is presented. In this approach, experts' preferences are mapped as points into two-dimensional planes, with the plant growth simulation algorithm (PGSA) being employed to calculate the optimal rally points, which are inversely mapped to IVIFNs to establish the collective matrix. In the study, four different methods are used to address one example problem to illustrate the feasibility and effectiveness of the proposed approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3010-3025
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• 2016

Lattice reduction (LR) has been used widely in conventional multiple-input multiple-output (MIMO) systems to enhance the performance. However, LR is hard to be applied to the relay systems which are important but more complicated in the wireless communication theory. This paper introduces a new viewpoint for utilizing LR in multiuser MIMO relay systems. The vector precoding (VP) is designed along with zero force (ZF) criterion and minimum mean square error (MMSE) criterion and enhanced by LR algorithm. This implementable precoder design combines nonlinear processing at the base station (BS) and linear processing at the relay. This precoder is capable of avoiding multiuser interference (MUI) at the mobile stations (MSs) and achieving excellent performance. Moreover, it is shown that the amount of feedback information is much less than that of the singular value decomposition (SVD) design. Simulation results show that the proposed scheme using the complex version of the Lenstra--Lenstra--Lovász (LLL) algorithm significantly improves system performance.

• The Research Journal of the Costume Culture
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• v.4 no.2
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• pp.173-185
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• 1996

The purpose of this study was to identify the relationship of clothing involvement and clothing buying behavior of women. A questionnaire was developed to measure clothing involvement, clothing purchasing motives, clothing purchasing criteria, fashion information sources, store selection criteria, and demographic characteristics. The questionnaire was administered to 430 female adults in Taegu. The data were analyzed using percentage, frequency, factor analysis, and t-test. The results of the study were s follows: 1. Subjects were divided into low clothing involved and high clothing involved groups. 2. Three dimensions of clothing purchasing motives were derived by factor analysis such as Aesthetic dependant, Impulsive, and Practical motive. Clothing purchasing criteria were factor analysed as Aesthetic, Qualitative, External, and Economical criterion. Fashion information sources were factor analysed as Printed & audio-visual oriented media, Marketer intensive search, Store search, Observation & Interpersonal search, and Experience. Store selection criteria were factor analyzed as Merchandise & Store atmosphere, Store convenience, and Brand & fashion. 3. There were significant differences between high involved and low involved consumers in clothing purchasing behavior. The high involved consumers showed more importance than low involved consumers about purchasing criteria expecially in aesthetic dependant. The high involved consumers put more importance to aesthetic, qualitative, and external criterion as clothing purchasing criteria. The high involved information sources. The high involved consumers were more concerned about merchandise & store atmosphere, and brand & fashion than low involved consumers in store selection criteria.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.247-252
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• 2015

Adaptive algorithms based on the criterion of zero-error probability (ZEP) have robustness to impulsive noise and their decision feedback (DF) versions are known to compensate effectively for severe multipath channel distortions. However the ZEP-DF algorithm computes several summation operations at each iteration time for each filter section and this plays an obstacle role in practical implementation. In this paper, the ZEP-DF with recursive gradient estimation (RGE) method is proposed and shown to reduce the computational burden of O(N) to a constant which is independent of the sample size N. Also the weight update of the initial state and the steady state is a continuous process without bringing about any propagation of gradient estimation error in DF structure.

• Communications for Statistical Applications and Methods
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• v.27 no.2
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• pp.189-199
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• 2020

This paper studies a Bayesian ordered multiple linear regression model with skew normal error. It is reasonable that the kind of inherent information available in an applied regression requires some constraints on the coefficients to be estimated. In addition, the assumption of normality of the errors is sometimes not appropriate in the real data. Therefore, to explain such situations more flexibly, we use the skew-normal distribution given by Sahu et al. (The Canadian Journal of Statistics, 31, 129-150, 2003) for error-terms including normal distribution. For Bayesian methodology, the Markov chain Monte Carlo method is employed to resolve complicated integration problems. Also, under the improper priors, the propriety of the associated posterior density is shown. Our Bayesian proposed model is applied to NZAPB's apple data. For model comparison between the skew normal error model and the normal error model, we use the Bayes factor and deviance information criterion given by Spiegelhalter et al. (Journal of the Royal Statistical Society Series B (Statistical Methodology), 64, 583-639, 2002). We also consider the problem of detecting an influential point concerning skewness using Bayes factors. Finally, concluding remarks are discussed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.502-503
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• 2019

In the existing system that recommends through review data analysis, it does not reflect personal preference details such as user's characteristics or product purchase tastes, in this paper, we propose a system that provides customized recommendation information to various users by selecting the criterion that the user thinks most importantly when searching for the product and purchasing the product, and analyzing it. This is because the user's personal preference is reflected by arranging the product list based on the criterion that the user occupies the largest portion of the product purchase, so that it is more efficient than the recommendation through the recommendation system.