• Proceedings of the KSPS conference
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• 2003.05a
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• pp.101-104
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• 2003

The purpose of this study was to compare acoustic differences of fricative /s/ between the dysarthric subjects and normal subjects. In additional, the subjects' speeches were evaluated in terms of word intelligibility containing /s/ and perceptual severity. Acoustic parameters were duration, peak frequency and intensity of /s/. The results showed that the first peak frequency and intensity of /s/ were significantly different between dysarthric subjetcts and normal subjects. Second, peceptual parameters were significantly different between dysarthric subjetcts and normal subjects. The Pearson correlation coefficient was used to determine the relationship between the acoustical and perceptual data. The results showed that there was a strong correlation between perceptual parameters and peak frequency of /s/.

• Geomechanics and Engineering
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• v.37 no.5
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• pp.475-498
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• 2024

The prediction of the susceptibility of soil to liquefaction using a limited set of parameters, particularly when dealing with highly unbalanced databases is a challenging problem. The current study focuses on different ensemble learning classification algorithms using highly unbalanced databases of results from in-situ tests; standard penetration test (SPT), shear wave velocity (V_s) test, and cone penetration test (CPT). The input parameters for these datasets consist of earthquake intensity parameters, strong ground motion parameters, and in-situ soil testing parameters. liquefaction index serving as the binary output parameter. After a rigorous comparison with existing literature, extreme gradient boosting (XGBoost), bagging, and random forest (RF) emerge as the most efficient models for liquefaction instance classification across different datasets. Notably, for SPT and V_s-based models, XGBoost exhibits superior performance, followed by Light gradient boosting machine (LightGBM) and Bagging, while for CPT-based models, Bagging ranks highest, followed by Gradient boosting and random forest, with CPT-based models demonstrating lower G_mean(error), rendering them preferable for soil liquefaction susceptibility prediction. Key parameters influencing model performance include internal friction angle of soil (ϕ) and percentage of fines less than 75 µ (F₇₅) for SPT and V_s data and normalized average cone tip resistance (q_c) and peak horizontal ground acceleration (a_max) for CPT data. It was also observed that the addition of V_s measurement to SPT data increased the efficiency of the prediction in comparison to only SPT data. Furthermore, to enhance usability, a graphical user interface (GUI) for seamless classification operations based on provided input parameters was proposed.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.12
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• pp.21-26
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• 2004

In this paper, a direct method is developed to extact RF equivalent circuit of a packaged BJT without optimization. First, parasitic components of plastic package are removed from measured S-parameters using open and short package patterns. Using package do-embedded S-parameters, a direct and simple method is proposed to extract bonding wire inductance and chip pad capacitance between package lead and chip pad. The small-signal model parameters of internal BJT are next determined by Z and Y-parameter formula derived from RF equivalent circuit. The modeled S-parameters of packaged BJT agree well with measured ones, verifying the accuracy of this new extraction method.

• Journal of Korean Neurosurgical Society
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• v.58 no.4
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• pp.357-362
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• 2015

Objective : To investigate risk factors for S1 screw loosening after lumbosacral fusion, including spinopelvic parameters and paraspinal muscles. Methods : We studied with 156 patients with degenerative lumbar disease who underwent lumbosacral interbody fusion and pedicle screw fixation including the level of L5-S1 between 2005 and 2012. The patients were divided into loosening and non-loosening groups. Screw loosening was defined as a halo sign larger than 1 mm around a screw. We checked cross sectional area of paraspinal muscles, mean signal intensity of the muscles on T2 weight MRI as a degree of fatty degeneration, spinopelvic parameters, bone mineral density, number of fusion level, and the characteristic of S1 screw. Results : Twenty seven patients showed S1 screw loosening, which is 24.4% of total. The mean duration for S1 screw loosening was $7.3{\pm}4.1$ months after surgery. Statistically significant risk factors were increased age, poor BMD, 3 or more fusion levels (p<0.05). Among spinopelvic parameters, a high pelvic incidence (p<0.01), a greater difference between pelvic incidence and lumbar lordotic angle preoperatively (p<0.01) and postoperatively (p<0.05). Smaller cross-sectional area and high T2 signal intensity in both multifidus and erector spinae muscles were also significant muscular risk factors (p<0.05). Small converging angle (p<0.001) and short intraosseous length (p<0.05) of S1 screw were significant screw related risk factors (p<0.05). Conclusion : In addition to well known risk factors, spinopelvic parameters and the degeneration of paraspinal muscles also showed significant effects on the S1 screw loosening.

• Journal of Advanced Marine Engineering and Technology
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• v.36 no.4
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• pp.497-503
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• 2012

The aim of this study was to optimize S-tube shape of heat exchanger in term of reducing the size of tube bundle and improving the mechanical properties such as the thermal stress and resonance. The geometric parameters such as offset length, the straight distance between one end and other end of tube, the tube length in straight portion and fillet radius was assessed as a valid parameters. The structural analysis was performed to estimate the structural characteristics. Main effect analysis was performed to investigate the main effect for the various geometric parameters. The response surface methodology was employed to establish mathematical approximation models as a function of the geometric parameters of the S-tube. Also, The optimization was performed to optimize geometric parameters of S-tube using the regression equations and optimization tool. The optimized tube shape has been proposed. Those could be used in the heat exchanger design used in high temperature.

• Korean Journal of Radiology
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• v.25 no.1
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• pp.43-54
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• 2024

Objective: To evaluate the added value of diffusion-weighted imaging (DWI)-based quantitative parameters to distinguish uterine sarcomas from atypical leiomyomas on preoperative magnetic resonance imaging (MRI). Materials and Methods: A total of 138 patients (age, 43.7 ± 10.3 years) with uterine sarcoma (n = 44) and atypical leiomyoma (n = 94) were retrospectively collected from four institutions. The cohort was randomly divided into training (84/138, 60.0%) and validation (54/138, 40.0%) sets. Two independent readers evaluated six qualitative MRI features and two DWI-based quantitative parameters for each index tumor. Multivariable logistic regression was used to identify the relevant qualitative MRI features. Diagnostic classifiers based on qualitative MRI features alone and in combination with DWI-based quantitative parameters were developed using a logistic regression algorithm. The diagnostic performance of the classifiers was evaluated using a cross-table analysis and calculation of the area under the receiver operating characteristic curve (AUC). Results: Mean apparent diffusion coefficient value of uterine sarcoma was lower than that of atypical leiomyoma (mean ± standard deviation, 0.94 ± 0.30 10^-3 mm²/s vs. 1.23 ± 0.25 10^-3 mm²/s; P < 0.001), and the relative contrast ratio was higher in the uterine sarcoma (8.16 ± 2.94 vs. 4.19 ± 2.66; P < 0.001). Selected qualitative MRI features included ill-defined margin (adjusted odds ratio [aOR], 17.9; 95% confidence interval [CI], 1.41-503, P = 0.040), intratumoral hemorrhage (aOR, 27.3; 95% CI, 3.74-596, P = 0.006), and absence of T2 dark area (aOR, 83.5; 95% CI, 12.4-1916, P < 0.001). The classifier that combined qualitative MRI features and DWI-based quantitative parameters showed significantly better performance than without DWI-based parameters in the validation set (AUC, 0.92 vs. 0.78; P < 0.001). Conclusion: The addition of DWI-based quantitative parameters to qualitative MRI features improved the diagnostic performance of the logistic regression classifier in differentiating uterine sarcomas from atypical leiomyomas on preoperative MRI.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2002.03a
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• pp.20-27
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• 2002

Conventional Levenberg-Marquardt's nonlinear inversion method is simply modified by taking into account the second derivatives of the Hessian matrix so as to give robust inversion results. The weight of the second derivative terms is determined by the value of so-called λ in Levenberg-Marquardt's method. The new inversion method is applied to observed data from small-to-moderate earthquakes to simultaneously evaluate the modes parameters of the stochastic point-source model in and around the Korean Peninsula. Best estimates of the stochastic model parameters are obtained along with their statistics and compared with the previous results. Overall characteristics of the model parameters are found to be more of those of interplate than intraplate tectonic region.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.7
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• pp.156-161
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• 1996

Accurate equivalent circuit modeling using multi-circuit optimization has been perfomred for detemining small-signal model of AlGaAs/GaAs HBTs. Three equivalent circuits for a cutoff biasing and two active biasing at different curretns are optimized simultaneously to fit gheir S parameters under the physics-based constrain that current-dependent elements for one of active circuits are connected to those for another circit multiplied by the ratio of two currents. The cutoff mode circuit and the physical constrain give the advantage of extracting physically acceptable parameters, because the number of unknown variables. After this optimization, three ses of optimized model S-parameters agree well with their measured S-parameters from 0.045 GHz to 26.5GHz.

• Journal of electromagnetic engineering and science
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• v.15 no.4
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• pp.258-265
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• 2015

A de-embedding method for multiport networks, especially for coupled odd interconnection lines, is presented in this paper. This method does not require a conversion from S-parameters to T-parameters, which is widely used in the de-embedding technique of multiport networks based on cascaded simple two-port relations, whereas here, we apply an operation to the S-matrix to generate all the uncoupled and coupled coefficients. The derivation of the method is based on the relations of incident and reflected waves between the input of the entire network and the input of the intrinsic device under test (DUT). The characteristics of the intrinsic DUT are eventually achieved and expressed as a function of the S-parameters of the whole network, which are easily obtained. The derived coefficients constitute ABCD-parameters for a convenient implementation of the method into cascaded multiport networks. A validation was performed based on a spice-like circuit simulator, and this verified the proposed method for both uncoupled and coupled cases.

• Journal of Power System Engineering
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• v.3 no.1
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• pp.67-73
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• 1999

It is not easy to control the speed of AC motors accurately without modeling with some parameters for the controlled system. However, there are some application parts which do not require high speed responses strictly and the motor parameters can not to be identified simply. In this paper, a speed control method for a synchronous motor(S.M) with unknown parameters of the motor is investigated. The method is based on the current control algorithm. Speed controller and current controller are designed using PI control law. Some experiments are performed using DSP and power expert system to prove the validity of the proposed method. Throughout experimental results, the method is confirmed successfully. This method is expected to control the system with unknown parameters of the S.M efficiently.