• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.8
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• pp.1265-1271
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• 2017

In this paper, the speech parameter fusion method is studied to improve the performance of the conventional emotion recognition system. For this purpose, the combination of the parameters that show the best performance by combining the cepstrum parameters and the various pitch parameters used in the conventional emotion recognition system are selected. Various pitch parameters were generated using numerical and statistical methods using pitch of speech. Performance evaluation was performed on the emotion recognition system using Gaussian mixture model(GMM) to select the pitch parameters that showed the best performance in combination with cepstrum parameters. As a parameter selection method, sequential feature selection method was used. In the experiment to distinguish the four emotions of normal, joy, sadness and angry, fifteen of the total 56 pitch parameters were selected and showed the best recognition performance when fused with cepstrum and delta cepstrum coefficients. This is a 48.9% reduction in the error of emotion recognition system using only pitch parameters.

• 유체기계공업학회:학술대회논문집
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• 2005.12a
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• pp.331-337
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• 2005

This study aims at evaluation of component performance of a commercial micro gas turbine by detailed measurements of various system parameters. A test facility to measure performance of a micro gas turbine was set up. Performance parameters such as turbine exit temperature, exhaust gas temperature, engine inlet temperature, compressor discharge pressure and fuel flow rate were measured. Variations in measured data and estimated performance parameters were analyzed. In addition to overall engine performance, component characteristic parameters including the turbine inlet temperature, the compressor efficiency, the turbine efficiency, the recuperator effectiveness were estimated. Behaviors of the estimated characteristic parameters with operating condition change were examined.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.374-388
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• 2022

Database systems usually have many parameters that must be configured by database administrators and users. RocksDB achieves fast data writing performance using a log-structured merged tree. This database has many parameters associated with write and space amplifications. Write amplification degrades the database performance, and space amplification leads to an increased storage space owing to the storage of unwanted data. Previously, it was proven that significant performance improvements can be achieved by tuning the database parameters. However, tuning the multiple parameters of a database is a laborious task owing to the large number of potential configuration combinations. To address this problem, we selected the important parameters that affect the performance of RocksDB using random forest. We then analyzed the effects of the selected parameters on write and space amplifications using analysis of variance. We used a genetic algorithm to obtain optimized values of the major parameters. The experimental results indicate an insignificant reduction (-5.64%) in the execution time when using these optimized values; however, write amplification, space amplification, and data processing rates improved considerably by 20.65%, 54.50%, and 89.68%, respectively, as compared to the performance when using the default settings.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.3
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• pp.241-245
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• 2001

In this paper, we present parameter optimization technique for GaAs/AlGaAs multiple quantum well avalanche photodiodes used for image capture mechanism in high-definition system. Even under flawless environment in semiconductor manufacturing process, random variation in process parameters can bring the fluctuation to device performance. The precise modeling for this variation is thus required for accurate prediction of device performance. The precise modeling for this variation is thus required for accurate prediction of device performance. This paper will first use experimental design and neural networks to model the nonlinear relationship between device process parameters and device performance parameters. The derived model was then put into genetic algorithms to acquire optimized device process parameters. From the optimized technique, we can predict device performance before high-volume manufacturign, and also increase production efficiency.

• The KSFM Journal of Fluid Machinery
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• v.8 no.5 s.32
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• pp.13-21
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• 2005

This study aims to analyze operating performance of a micro gas turbine with the aid of detailed measurements of various system parameters. In addition to embedded measurements, parameters such as exhaust temperatures, engine inlet temperatures and fuel flow rates are measured. Variations in measured data and estimated performance parameters are analyzed. Those data are processed to calculate losses along the power transmission line and the net gas turbine performance (power and efficiency based on the gas turbine shaft end) is isolated from the overall system performance. A method to estimate characteristic parameters such as component efficiencies, based on the comparison between measured and predicted performance data, is suggested and exemplified for the full load condition.

• 유체기계공업학회:학술대회논문집
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• 2004.12a
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• pp.132-139
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• 2004

This study aims to analyze operating performance of a micro gas turbine with the aid of detailed measurements of various system parameters. In addition to embedded measurements, parameters such as exhaust temperatures, engine inlet temperatures and fuel flow rates are measured Variations in measured data and estimated performance parameters are analyzed. Those data are processed to calculate losses along the power transmission line and the net gas turbine performance (power and efficiency based on the gas turbine shaft end) is isolated from the overall system performance. On the basis of the measured data, analytical approach is tried to estimate design characteristic and performance parameters such as component efficiencies and unmeasured temperatures.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.149-152
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• 2003

In this paper, we present a performance comparison of feature parameters and classifiers for speech/music discrimination. Experiments were carried out on six feature parameters and three classifiers. It turns out that three classifiers shows similar performance. The feature set that captures the temporal and spectral structure of the signal yields good performance, while the phone-based feature set shows relatively inferior performance.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.6
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• pp.1464-1473
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• 1990

Optimal design parameters are estimated from the sensitivity function and performance index variation. Suspension design modification for performance improvement and basic materials for practical applications are presented. The linear quarter model of a vehicle suspension is analyzed in order to represent the utilities of sensitivity analysis, and sensitivity function is determined in the frequency domain. The change of frequency response function is predicted, which depends on the design parameter variation and the property is verified by computer simulation. As an investigation results of sensitivity function for the vibrational amplitude of sprung mass to road profile input, it is shown that the most sensitive parameters are the suspension damping and the suspension stiffness. In order to identify the effects of these two parameters to the performance of suspension system, the performance index variation according to the changes of parameters is considered and then optimal design parameters are determined. It is verified that the system response is improved noticeably in the both of frequency and time domain after the design modification with the optimal parameters.

• Aerospace Engineering and Technology
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• v.1 no.2
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• pp.66-74
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• 2002

The characteristics of the satellite image quality parameters driven by satellite imaging instrument are investigated. Since the satellite image is directly produced by the satellite imaging instrument, the satellite image quality depends on the imager performance highly. This is why the imager performance parameters are considered as an important part of the satellite image quality parameters. The imager performance parameters consist of spectral band parameters, ground sample distance(GSD) parameters, swath width parameters, imager Modulation Transfer Function (MTF), imager Signal to Noise Ratio(SNR), radiometric response characteristics parameters, pixel registration, and imager calibration.

• 유체기계공업학회:학술대회논문집
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• 1998.12a
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• pp.57-63
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• 1998

The performance of a centrifugal fan depends on the dimensional parameters of impeller, such as the inlet and exit diameter, area ratio, relative flow angles to the blade, and number of blades. These design parameters, however, are inter-related, so it is very difficult to identify the effect of each parameter to the fan performance. In this experimental study the effect of the design parameters on the performance of a small centrifugal impeller being used for vacuum cleaners are investigated. Total 30 shrouded impellers with 120mm diameter were tested and the results were non-dimensionalized to compare their performance.