• Journal of Mechanical Science and Technology
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• v.17 no.4
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• pp.484-491
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• 2003

For most of linear time-varying (LTV) systems, it is difficult to design time-varying controllers in analytic way. Accordingly, by approximating LTV systems as uncertain linear time-invariant, control design approaches such as robust control have been applied to the resulting uncertain LTI systems. In particular, a robust control method such as quantitative feedback theory (QFT) has an advantage of guaranteeing the frozen-time stability and the performance specification against plant parameter uncertainties. However, if these methods are applied to the approximated linear. time-invariant (LTI) plants with large uncertainty, the resulting control law becomes complicated and also may not become ineffective with faster dynamic behavior. In this paper, as a method to enhance the fast dynamic performance of LTV systems with bounded time-varying parameters, the approximated uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial basis function (RBF) networks.

• Journal of the Korean Society of Safety
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• v.31 no.4
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• pp.48-54
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• 2016

The prediction of various emissions from coal combustion is an important subject of researchers and engineers because of environmental consideration. Therefore, the development of the models for predicting pollutants very fast has received much attention from international research community, especially in the field of safety assessment. In this work, response surface method was introduced as a design of experiment, and the database for RSM was set with the numerical simulation of a drop tube furnace (DTF) to predict the spatial distribution of pollutant concentrations as well as final ones. The distribution of carbon dioxide in DTF was assumed to have Boltzman function, and the resulted function with parameters of a high $R^2$ value facilitates predicting an accurate distribution of $CO_2$. However, CO distribution had a difference near peak concentration when Gaussian function was introduced to simulate the CO distribution. It might be mainly due to the anti-symmetry of the CO concentration in DTF, and hence Extreme function was used to permit the asymmetry. The application of Extreme function enhanced the regression accuracy of parameters and the prediction was in a fairly good agreement with the new experiments. These results promise the wide use of statistical models for the quantitative safety assessment.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.498-503
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• 1994

The paper demonstrates that holon networks can be used effectively for identification of nonlinear dynamical systems. The emphasis of the paper is on modeling of complicated systems which have a great deal of uncertainty and unknown interactions between their elements and parameters. The concept of applying a quantitative model building, for example, to environmental or ecological systems is not new. In a previous paper we presented a holon network model as an another alternative to quantitative modeling. Holon networks have a hierarchical construction where each level of hierarchy consists of networks with reciprocal actions among their elements. The networks are able to evolve by self-organizing their structure and adapt their parameters to environments. This was achieved by an autonomous decentralized adaptation algorithm. In this paper we propose a new emergent evolution algorithm. In this algorithm the initial holon networks consists of only a few elements and it grows gradually with each new observation in order to fit their function to the environment. Some examples show that this algorithm can lead to a network structure which has sufficient flexibility and adapts well to the environment.

• The Journal of Information Technology
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• v.2 no.2
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• pp.13-22
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• 1999

In this paper, we purpose automatic diagnosis in online, as the fundamental study to diagnose the partial discharge mechanism and to predict the lifetime by introduction a neural network. In the proposed method, we use AE(acoustic emission) sensing system and calculate a quantitative statistic parameter by pulse number and amplitude. Using statically parameters such as the center of gravity(G) and the gradient if the discharge distribute(C), we analyzed the early stage and the middle stage. the quantitative statistic parameters are learned by a neural network. The diagnosis of insulation degradation and a lifetime prediction by the early stage time are achieved. On the basis of revealed excellent diagnosis ability through the neural network learning for the patterns during degradation, it was proved that the neural network is appropriate for degradation diagnosis and lifetime prediction in partial discharge.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.4
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• pp.959-966
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• 2010

Quantitative ultrasound analysis provides fundamental information of various ultrasound parameters using spectral information of the short-gated radiofrequency(RF) data. Therefore, accurate extraction of spectral information from backscattered RF signal is crucial for further analysis of medical ultrasound parameters. In this paper, we propose two techniques for calculating a more accurate power spectrum which are based on the phase-compensation using the normalized cross-correlation to minimize estimation errors due to phase variations, and the weighted averaging technique to maximize the signal-to-noise ratio(SNR). The simulation results demonstrate that the proposed method estimates better results with 10% smaller estimation variances compared to the conventional methods.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.6
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• pp.813-819
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• 2014

The purpose of this study was to extract accurate parameters of facial movement features using 3-D motion capture system in speech recognition technology through lip-reading. Instead of using the features obtained through traditional camera image, the 3-D motion system was used to obtain quantitative data for actual facial movements, and to analyze 11 variables that exhibit particular patterns such as nose, lip, jaw and cheek movements in monosyllable vocalizations. Fourteen subjects, all in 20s of age, were asked to vocalize 11 types of Korean vowel monosyllables for three times with 36 reflective markers on their faces. The obtained facial movement data were then calculated into 11 parameters and presented as patterns for each monosyllable vocalization. The parameter patterns were performed through learning and recognizing process for each monosyllable with speech recognition algorithms with Hidden Markov Model (HMM) and Viterbi algorithm. The accuracy rate of 11 monosyllables recognition was 97.2%, which suggests the possibility of voice recognition of Korean language through quantitative facial movement analysis.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.6
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• pp.477-487
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• 2005

As embedded system grows in size and complexity, the importance of the technique for dynamic memory allocation has increased. The objective of this paper is to measure the performance of dynamic memory allocation by varying both hardware and software design parameters for embedded systems. Unlike torrent performance evaluation studies that have presumed the single threaded system with single address spate without OS support, our study adopts realistic environment where the embedded system runs on Linux OS. This paper contains the experimental performance analyses of dynamic memory allocation method by investigating the effects of each software layer and some hardware design parameters. Our quantitative results tan be used to help system designers design high performance, low power embedded systems.

• Geomechanics and Engineering
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• v.30 no.5
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• pp.449-460
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• 2022

Safe underground construction in a rock mass requires adequate ground investigation and effective determination of rock conditions. The estimation of rock mass behavior is difficult, because rock masses are innately anisotropic and heterogeneous at different scales and are affected by various environmental factors. Quantitative rock mass classification systems, such as the Q-system and rock mass rating, are widely used for characterization and engineering design. The measurement of rock classification parameters is subjective and can vary among observers, resulting in questionable accuracy. Geophysical investigation methods, such as seismic surveys, have also been used for ground characterization. Torsional shear wave propagation characteristics in cylindrical rods are equal to that in an infinite media. A probabilistic quantitative relationship between the Q-value and shear wave velocity is thus investigated considering long-wavelength wave propagation in equivalent continuum jointed rock masses. Individual Q-system parameters are correlated with stress-dependent shear wave velocities in jointed rocks using experimental and numerical methods. The relationship between the Q-value and the shear wave velocity is normalized using a defined reference condition. This relationship is further improved using probabilistic analysis to remove unrealistic data and to suggest a range of Q-values for a given wave velocity. The proposed probabilistic Q-value estimation is then compared with field measurements and cross-hole seismic test data to verify its applicability.

• Korean Journal of Biological Psychiatry
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• v.23 no.4
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• pp.193-198
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• 2016

Objectives Obsessive-compulsive disorder (OCD) and schizophrenia have many common clinical and neurocognitive features. However, not all of them share the same underlying mechanism. The aim of this study was to discover evidences that indicate a pathophysiological mechanism specific to OCD by comparing correlations of quantitative electroencephalography (QEEG) patterns and neurocognitive function in patients with OCD and schizophrenia. Methods Resting-state QEEG data of total 265 patients were acquired retrospectively and parameters such as absolute power, relative power and peak frequency were analyzed from the data. Stroop test and Trail Making Test results as well as demographic features were reviewed for this study. The correlation of neurocognitive functions and brain electrical activities in each group were assessed and compared by correlation analysis. Results Compared with the OCD group, the schizophrenia group performed poorly in neurocognitive tests. Mean values of QEEG parameters in patients with OCD and schizophrenia did not show significant differences. Both absolute and relative power of alpha rhythm in central and frontal regions showed significant positive correlation with Stroop test results in OCD patients. Conclusions Findings in this study shows distinctive correlations between frontal executive dysfunction and frontal alpha rhythm in the OCD patients, both of which might be a candidate for endophenotype underlying obsessive rumination.

• Journal of Veterinary Clinics
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• v.31 no.5
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• pp.376-381
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• 2014

In this study, we analyzed the computed tomography (CT) measurements of lung volume and density in dogs with relation to body weight, age, sex, and breed. The multi-detector CT examination of the thorax was performed on dogs without respiratory or cardiovascular diseases. Three-dimensional reconstruction of CT images facilitated measurement of lung volume and density. There was a statistical significant correlation between body weight and lung volume (p < 0.0001). Lung density significantly decreased with an increase in body weight (p = 0.0078). However, no correlation was seen between these lung parameters and either sex or age of the dogs. In conclusion, this study shows that body weight is an important factor to consider when interpreting total lung volume and density values measured by quantitative CT. We highlight the need for further study using quantitative CT in identifying the potential effects of sex, age, and disease status on these parameters.