• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.848-855
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• 2011

This paper proposes a method to reduce the limit cycle phenomenon that appears in the steady-state response of a pendubot system, when it is controlled by a state feedback controller based on the linearized system model. For this, we employed the compensator which estimates the friction based on the LuGre model in the LQR control. The proposed compensation method is validated by experiments for a pendubot system, which shows that the external disturbance as well can be efficiently compensated.

• Journal of Mechanical Science and Technology
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• v.20 no.4
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• pp.437-446
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• 2006

Laser vision inspection systems are becoming popular for automated inspection of manufactured components. The performance of such systems can be enhanced by improving accuracy of the hardware and robustness of the software used in the system. This paper presents a new approach for enhancing the capability of a laser vision system by applying hardware compensation and using efficient analysis software. A 3D geometrical model is developed to study and compensate for possible distortions in installation of gantry robot on which the vision system is mounted. Appropriate compensation is applied to the inspection data obtained from the laser vision system based on the parameters in 3D model. The present laser vision system is used for dimensional inspection of car chassis sub frame and lower arm assembly module. An algorithm based on simplex search techniques is used for analyzing the compensated inspection data. The details of 3D model, parameters used for compensation and the measurement data obtained from the system are presented in this paper. The details of search algorithm used for analyzing the measurement data and the results obtained are also presented in the paper. It is observed from the results that, by applying compensation and using appropriate algorithms for analyzing, the error in evaluation of the inspection data can be significantly minimized, thus reducing the risk of rejecting good parts.

• The Journal of the Acoustical Society of Korea
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• v.37 no.6
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• pp.506-511
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• 2018

This paper proposes an GMM(Gaussian Mixture Model)-DNN(Deep Neural Network) hybrid-based feature compensation method for effective speech recognition in noisy environments. In the proposed algorithm, the posterior probability for the conventional GMM-based feature compensation method is calculated using DNN. The experimental results using the Aurora 2.0 framework and database demonstrate that the proposed GMM-DNN hybrid-based feature compensation method shows more effective in Known and Unknown noisy environments compared to the GMM-based method. In particular, the experiments of the Unknown environments show 9.13 % of relative improvement in the average of WER (Word Error Rate) and considerable improvements in lower SNR (Signal to Noise Ratio) conditions such as 0 and 5 dB SNR.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.3
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• pp.16-23
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• 2004

Thermally induced errors of machine tools have been recognized as one of the most important issues in precision machining. This is probably the most formidable obstacle to obtain high level of machining accuracy. To this regard, the experimental compensation methodologies such as software-based method or origin shift of machine tool axes have been suggested. In this research, to cope with thermal deformation, a model based correction was carried out with the function of an external machine coordinate shift. Models with multi-linear regression or neural network were investigated to selected a good one for thermal compensation. Consequently, multi-linear regression model combined with origin shift was verified good enough form the machining of dot matrices of plate with ball end milling.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.1
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• pp.129-138
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• 2015

The problems associated with the excessive compensation of the public organizations in Korea have been presented not only by the press but also by the academic societies, including the management evaluation team of the public organizations, both in Korea and abroad. To analyze whether the compensation is excessive necessitates the empirical study on the present condition of the compensation system of the public organizations. Therefore, the purpose of this paper is to suggest the issues and the future directions of the compensation in the public organizations. The findings from the analysis of the data collected in this research include the expansion of the difference in compensation, the reinforcement of the job and performance-based compensation, the systematization of the model on the base compensation, and the differentiation of the compensation increase based on productivity.

• Korea Journal of Hospital Management
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• v.4 no.2
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• pp.162-191
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• 1999

This study was conducted to establish finance performance evaluation model for physicians in each clinical department, by using factors which determines financial outcome(performance) in each clinical department The ultimate aim of study is to develop effective performance-based pay system for physicians. The system, by motivating physicians, should increase their productivity. To do so, it is critical to establish finance performance evaluation model to achieve final goal of this study. 232 private hospitals were chosen from 693 hospitals which were subject to hospital survey by the Korea Institute of Health Services Management and their revenue and expense-related data during 1997 were collected. By adopting multiple regression method, the study shows that the evaluation model for each clinical department was statistically significant. The study suggest the effective performance-based pay system based on financial performance of each clinical department. The pay system includes the level of compensation, the way of how to allocate profits to each department, and criteria whether the compensation should provide or not. In conclusion, the study has following implications. First, the study suggest finance performance evaluation model for each clinical department Second, the study suggest guidelines and plans to establish qualitative measure of financial performance in each clinical department. Third, the study suggest that adopting performance-based pay for physicians could be impetus to achieve organizational goal by motivating them with fair compensation.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.215-218
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• 2003

In this paper we apply PMC (parallel model combination) to speech recognition system online. As a representative of model based noise compensation techniques, PMC compensates environmental mismatch by combining pretrained clean speech models and real-time estimated noise information. This is very effective approach for compensating extreme environmental mismatch but is inadequate to use in on-line system for heavy computational cost. To reduce the computational cost and to apply PMC online, we use a noise masking effect - the energy in a frequency band is dominated either by clean speech energy or by noise energy - in the process of model compensation. Experiments on artificially produced noisy speech data confirm that the proposed technique is fast and effective for the on-line model compensation.

• Safety and Health at Work
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• v.2 no.2
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• pp.148-157
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• 2011

Objectives: Although compensation for occupational injuries and diseases is guaranteed in almost all nations, countries vary greatly with respect to how they organize workers' compensation systems. In this paper, we focus on three aspects of workers' compensation insurance in Organization for Economic Cooperation and Development (OECD) countries - types of systems, employers' funding mechanisms, and coverage for injured workers - and their impacts on the actual frequencies of occupational injuries and diseases. Methods: We estimated a panel data fixed effect model with cross-country OECD and International Labor Organization data. We controlled for country fixed effects, relevant aggregate variables, and dummy variables representing the occupational accidents data source. Results: First, the use of a private insurance system is found to lower the occupational accidents. Second, the use of risk-based pricing for the payment of employer raises the occupational injuries and diseases. Finally, the wider the coverage of injured workers is, the less frequent the workplace accidents are. Conclusion: Private insurance system, fixed flat rate employers' funding mechanism, and higher coverage of compensation scheme are significantly and positively correlated with lower level of occupational accidents compared with the public insurance system, risk-based funding system, and lower coverage of compensation scheme.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.04a
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• pp.376-381
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• 2001

This paper presents a methodology of machining error compensation by using Artificial Neural Network(ANN) model based on the inspection database of On-Machine-Measurement(OMM) system. First, the geometric errors of the machining center and the probing errors are significantly reduced through compensation processes. Then, we acquire machining error distributions from a specimen workpiece. In order to efficiently analyze the machining errors, we define two characteristic machining error parameters. These can be modeled by using an ANN model, which allows us to determine the machining errors in the domain of considered cutting conditions. Based on this ANN model, we try to correct the tool path in order to effectively reduce the errors by using an iterative algorithm. The iterative algorithm allows us to integrate changes of the cutting conditions according to the corrected tool path. Experimentation is carried out in order to validate the approaches proposed in this paper.

• The Journal of the Acoustical Society of Korea
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• v.23 no.6
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• pp.473-480
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• 2004

In this paper we propose an effective feature compensation scheme based on the speech model in order to achieve robust speech recognition. The proposed feature compensation method is based on parallel combined mixture model (PCMM). The previous PCMM works require a highly sophisticated procedure for estimation of the combined mixture model in order to reflect the time-varying noisy conditions at every utterance. The proposed schemes can cope with the time-varying background noise by employing the interpolation method of the multiple mixture models. We apply the‘data-driven’method to PCMM tot move reliable model combination and introduce a frame-synched version for estimation of environments posteriori. In order to reduce the computational complexity due to multiple models, we propose a technique for mixture sharing. The statistically similar Gaussian components are selected and the smoothed versions are generated for sharing. The performance is examined over Aurora 2.0 and speech corpus recorded while car-driving. The experimental results indicate that the proposed schemes are effective in realizing robust speech recognition and reducing the computational complexities under both simulated environments and real-life conditions.