• Journal of the Korean Society for Precision Engineering
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• v.30 no.5
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• pp.507-512
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• 2013

This paper proposes a new model to compensate for errors of a five-axis machine tool. A matrix with error components, that is, an error matrix, is separated from the error synthesis model of a five-axis machine tool. Based on the kinematics and inversion of the error matrix which can be obtained not by using a numerical method, an error compensation model is established and used to calculate compensation values of joint variables. The proposed compensation model does not need numerical methods to find the compensation values from the error compensation model, which includes nonlinear equations. An experiment using a double ball-bar is implemented to verify the proposed model.

• Korea Journal of Hospital Management
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• v.10 no.4
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• pp.75-97
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• 2005

The research objective is to empirically investigate the compensation packages maximizing the utilities of internal customers by applying the market segmentation theory. Data was collected from four Korean hospitals in Seoul, Busan and Gyunggi-do. The research is designed to seek the compensation package maximizing the utility of doctors by mixture regression model, which has been applied as latent structure and other type of finite mixture models from various academic fields since early 1980s. The mixture regression model shows the optimal segments number and fuzzy classification for each observation by EM(expectation-maximization algorism). The finite mixture regression model is to unmix the sample, to identify the groups, and to estimate the parameters of the density function underlying the observed data within each group. The doctors were segmented into 5 groups by their preference for the compensation package. The results of this study imply that the utility of doctors increases with differentiated compensation package segmented by their preference.

• Speech Sciences
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• v.14 no.2
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• pp.115-126
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• 2007

There have been many research efforts to improve the performance of the speech recognizer in noisy conditions. Among them, the model compensation method and the speech enhancement approach have been used widely. In this paper, we propose to combine the two different approaches to further enhance the recognition rates in the noisy speech recognition. For the speech enhancement, the minimum mean square error-short time spectral amplitude (MMSE-STSA) has been adopted and the parallel model combination (PMC) and Jacobian adaptation (JA) have been used as the model compensation approaches. From the experimental results, we could find that the hybrid approach that applies the model compensation methods to the enhanced speech produce better results than just using only one of the two approaches.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.215-221
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• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.208.2-212
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• 1997

In a model based friction comensation for a frictional system,the performance of the system is inflenceed by the selection of the friction model. Especially, when a real plant have dynamic friction characteritics, the compensation of friction with a static friction model may deteriorate the perfomance. For the system we constlucted an adaptiv parameter estimation and friction compensation with a newly introduced dynamic friction model proposed by Canudas et.[1]. The model depicts varios frictional phenomena,such as Stibeck effect,frictional memory, Stick-slip motion. Parmeter identification algorithm are followed conventional RLSM adaptive rule. The stability for the closed system was proved by the Lyapunov stability. The result say that if a real system have dynamic friction property,the friction compensation with the dynamic friction model will improve the perfomance moreover static friction model based compensation may lead to the system unstable.

• Speech Sciences
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• v.11 no.2
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• pp.247-257
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• 2004

There has been many research efforts to overcome the problems of speech recognition in the noisy conditions. Among them, the model-based compensation methods such as the parallel model combination (PMC) and vector Taylor series (VTS) have been found to perform efficiently compared with the previous speech enhancement methods or the feature-based approaches. In this paper, a data-driven model compensation approach that adapts the HMM(hidden Markv model) parameters for the noisy speech recognition is proposed. Instead of assuming some statistical approximations as in the conventional model-based methods such as the PMC, the statistics necessary for the HMM parameter adaptation is directly estimated by using the Baum-Welch algorithm. The proposed method has shown improved results compared with the PMC for the noisy speech recognition.

• The Research Journal of the Costume Culture
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• v.26 no.3
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• pp.282-295
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• 2018

Hair style allows consumers to express their aesthetic sense and individual beauty. However, due to the attributes of hairdressing services and the high expectations of consumers, complaints are increasing rapidly. This study examined the complaint behavior, compensation and hair salon patronage of consumers. Then, a model is presented that explains the complaint behavior for hairstyling, forms of compensation, and hair salon patronage through empirical analysis. This study was conducted by a survey method. A total of 399 questionnaires were used for the analysis. The data were analyzed using SPSS 23.0 and AMOS 23.0 statistical software. The dimension of complaint behavior for hair style included verbal complaints, non-verbal complaints in the salon and private complaints outside the salon. The forms of compensation included re-procedure, psychological, and material compensation. Hair salon patronage was one-dimensional. These results were obtained through exploratory and confirmatory factor analysis. Then the conceptual model was empirically analyzed by covariance structure analysis and obtained in final form through model modification. Verbal complaint behavior positively influenced re-procedure compensation. In addition, non-verbal complaint behavior had positive effects on psychological and material compensation. Hair salon patronage was positively affected by re-procedure and psychological compensation. However, private complaint behavior had a negative effect on hair salon patronage. The direct and indirect effects of the paths among variables were verified by analyzing the mediating effects of different forms of compensations. It is possible to establish differentiated marketing strategies with these findings for consumers with complaint behaviors by considering the forms of compensation.

• Smart Structures and Systems
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• v.25 no.5
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• pp.569-580
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• 2020

The identification of delays and delay compensation are critical problems in real-time hybrid simulations (RTHS). Conventional delay compensation methods are mostly based on the assumption of a constant delay. However, the system delay may vary during tests owing to the nonlinearity of the loading system and/or the behavioral variations of the specimen. To address this issue, this study presents an adaptive delay compensation method based on a discrete model of the loading system. In particular, the parameters of this discrete model are identified and updated online with the least-squares method to represent a servo hydraulic loading system. Furthermore, based on this model, the system delays are compensated for by generating system commands using the desired displacements, achieved displacements, and previous displacement commands. This method is more general than the existing compensation methods because it can predict commands based on multiple displacement categories. Moreover, this method is straightforward and suitable for implementation on digital signal processing boards because it relies solely on the displacements rather than on velocity and/or acceleration data. The virtual and real RTHS results show that the studied method exhibits satisfactory estimation smoothness and compensation accuracy. Furthermore, considering the measurement noise, the low-order parameter models of this method are more favorable than that the high-order parameter models.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.2
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• pp.18-24
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• 2006

This paper proposes a LuGre Model-Based Neural Network (MBNN) friction compensation algorithm for a linear motor stage. For matching the friction phenomena in both the motion-start region and the motion-reverse region, the LuGre dynamic model is employed into the proposed compensation algorithm. After training of the model-based neural network is completed, the estimated friction for compensation is obtained. From the obtained result we find that the new structure gains advantage over the non-friction compensation system on the performance of the compensator in both regions. The proposed compensator is evaluated and compared experimentally with an uncompensated system on a microcomputer controlled linear motor tracking system in the final section of the paper. The experimental results show the improvement on the maximum velocity error and the root mean square tracking error in the motion-start region ranges from 34% to 53% and from 53% to 75% respectively, and in the motion-reverse region from 48% to 65% and from 79% to 90% respectively.

• Journal of Korean Academy of Nursing Administration
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• v.15 no.3
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• pp.325-335
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• 2009

Purpose: The purpose of this study was to examine the relationships among TQM activities, compensation equity, and performance in hospitals. This study was designed to construct a structural equation model of TQM activities, compensation equity, and performance. Method: The subjects were 239 personnels working in four hospitals in Daegu and Gyeongpook. Data were collected using structured questionnaire from October 4, 2007 to February 4, 2008. The collected data were analyzed using the SPSS 12.0 and AMOS 5.0 program. Result: The overall fitness of the structural equation model was evaluated. These results showed that the model was adequate. TQM activities directly influenced organizational performance and indirectly influenced organizational performance through compensation equity. Conclusion: In testing the structural equation model, the findings showed that TQM activities and compensation equity were important factors for improving organizational performance. Therefore, to improve performance, the hospital leaders must establish the strategies to facilitate TQM activities. It is also necessary to establish effective reward and performance appraisal systems to induce positive participation of personnels in hospitals.