• The Korean Journal of Nuclear Medicine
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• v.27 no.2
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• pp.239-247
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• 1993

Differentiating the various causes of hydronephrosis from that of obstruction can be very difficult. The decision-making process for those instances of urinary tract dilatation that require surgical correction and those that do not is based in part on the findings of diuresis renography. The methodology for performing this test has differed among nuclear medicine practitioners and the surgical findings are occasionally discrepant from the diuretic renogram interpretation. Consequently we made an automatic computer software program that calculates the slope of the response curve. The quantitative indices, such as the injection and response t1/2 by linear-fitting and monoexponential-fitting, were compared with the visual assessment of the diuretic cinerenography and clinical outcome in 50 children (62 kidneys) with ureteropelvic junction obstruction. Pooled diuresis renogram data indicated that: (1) Visual evaluation of the diuretic cinerenography is a sensitive (87%, 54/62) tool to differentiate obstruction in suspected ureteropelvic junction obstruction. (2) The cut-off value (maximum washout t1/2 with non-obstruction) of injection and response t1/2 by linear-fitting were 40 min. (3) The sensitivity and specificity using injection and response t1/2 by linear-fitting for obstruction were 89%(23/26) and 100%(30/30), respectively. (4) Response t1/2 as well as injection t1/2 by monoexponential-fitting do not stratify children with possible ureteropelivic junction obstruction. In conclusion, quantitative assessment of diuretic renography as well as visual assessment of diuretic cinerenography correlate well with surgical and clinical outcome of suspected ureteropelvic junction obstruction.

• Korean Journal of Optics and Photonics
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• v.20 no.1
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• pp.48-52
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• 2009

We make a simple electrically controllable linear polarization rotator over $360^{\circ}$ without loss by using a thick ECB(electrically controlled birefringence) liquid crystal cell and a quarter wave plate at 514.5 nm wavelength. Its operating principle can be analyzed and explained by using simple polarization analysis and experimental data. We demonstrate that the degree of polarization of the rotator is 0.964 and the temporal variation for 1 week lies within ${\pm}1$ degree. We can easily solve the problem of nonlinearity of the dependence of the rotational angle of linear polarization on the applied voltage by changing the utilized voltage range or its fitting curve.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1023-1024
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• 2011

This paper deals with an improved core loss calculation of Linear Oscillatory Motor from curve fitting method using modified Steinmetz equation considered anomalous loss. For an accurate calculation, magnetic field analyses in stator core considering, magnetic field analyses in stator core considering the time harmonics are performed. And using the nonlinear finite element analysis (FEM), we applied separated rotating and alternating magnetic filed to core loss calculation.

• Journal of Electrical Engineering and Technology
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• v.8 no.6
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• pp.1409-1414
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• 2013

A new calculation method for iron loss coefficients is proposed by using the Steinmetz equation from Epstein data. The hysteresis loss must have linear characteristic according to the frequency. However, the existing iron loss coefficients are defined by formula of frequency. In this case, the hysteresis loss has non-linear characteristics by frequency. So, in this paper, the iron loss coefficients were defined by a function of the magnetic flux density, and the iron loss calculation is applied for Interior Permanent Magnet Synchronous Motor(IPMSM) of 600(W) and 200(W). The iron loss calculation results and the experimental results are compared according to the various materials.

• Korean Journal of Veterinary Research
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• v.53 no.2
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• pp.73-76
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• 2013

The aim of this study was to produce a simple and inexpensive technique for estimating the obturator foramen area (OFA) from young calves based on the hypothesis that OFA can be extrapolated from simple linear measurements. Three linear measurements - dorsoventral height, craneocaudal width and total perimeter of obturator foramen - were obtained from 55 bovine hemicoxae. Different algorithms for determining OFA were then produced with a regression analysis (curve fitting) and statistical analysis software. The most simple equation was OFA ($mm^2$) = [3,150.538 + ($36.111^*CW$)] - [147,856.033/DH] (where CW = craneocaudal width and DH = dorsoventral height, both in mm), representing a good nonlinear model with a standard deviation of error for the estimate of 232.44 and a coefficient of multiple determination of 0.846. This formula may be helpful as a repeatable and easily performed estimation of the obturator foramen area in young bovines. The area of the obturator foramen magnum can thus be estimated using this regression formula.

• Communications for Statistical Applications and Methods
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• v.22 no.4
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• pp.349-359
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• 2015

We study a semiparametric Bayesian approach to small area estimation under a nested error linear regression model with area level covariate subject to measurement error. Consideration is given to radial basis functions for the regression spline and knots on a grid of equally spaced sample quantiles of covariate with measurement errors in the nested error linear regression model setup. We conduct a hierarchical Bayesian structural measurement error model for small areas and prove the propriety of the joint posterior based on a given hierarchical Bayesian framework since some priors are defined non-informative improper priors that uses Markov Chain Monte Carlo methods to fit it. Our methodology is illustrated using numerical examples to compare possible models based on model adequacy criteria; in addition, analysis is conducted based on real data.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.26 no.4
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• pp.263-279
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• 2022

This paper presents an automatic inspection of defects in semiconductor images. We devise a statistical method to find defects on homogeneous background from the observation that it has a log-normal distribution. If computer aided design (CAD) data is available, we use it to construct a signed distance function (SDF) and change the pixel values so that the average of pixel values along the level curve of the SDF is zero, so that the image has a homogeneous background. In the absence of CAD data, we devise a hybrid method consisting of a model-based algorithm and two neural networks. The model-based algorithm uses the first right singular vector to determine whether the image has a linear or complex structure. For an image with a linear structure, we remove the structure using the rank 1 approximation so that it has a homogeneous background. An image with a complex structure is inspected by two neural networks. We provide results of numerical experiments for the proposed methods.

• Investigative Magnetic Resonance Imaging
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• v.9 no.1
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• pp.36-42
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• 2005

Purpose : To develop a novel approach to calculate the sensitivity profiles of the phased array coil for use in non-uniform intensity correction. Materials and Methods : The proposed intensity correction method estimates the sensitivity profile of the coil to extract intensity variations that represent the scanned image. The sensitivity profile is estimated by fitting a non-linear curve to various angles of projections through the imaged object in order to eliminate the high-frequency image content. Filtered back projection is then used to compute the estimates of the sensitivity profile of each coil. The method was applied both to phantom and brain images from 8-channel phased-array coil and 4-channel phased-array coil, respectively. Results : Intensity-corrected images from the proposed method have more uniform intensity than those from the commonly used 'sum-of-squares' approach. By using the proposed correction method, the intensity variation was reduced to $6.1\%$ from $13.1\%$, acquired from the 'sum-of-squares'. Conclusion : The proposed method is more effective at correcting the intensity non-uniformity of the phased-array surface-coil images than the conventional 'sum-of-squares' method.

• The Korean Journal of Nuclear Medicine Technology
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• v.23 no.2
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• pp.43-50
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• 2019

Purpose The principle of nuclear medicine test is divided into two main categories: competition(radioimmunoassay, RIA) and noncompetitive reaction(Immunoradiometric assay, IRMA). It is known that the curve fitting method, which is commonly used in inspection field, uses Spline interpolation in RIA method and Linear interpolation method in IRMA method. Among them, the insulin test using the IRMA test showed a significant difference, especially at low concentrations, despite the same algorithm of linear interpolation between fully automated radio immunoassay analyzers. In this study, we aim to obtain results from applying two different of algorithm using fully automated radio immunoassay analyzers including Gamma pro, Gamma 10, Cobra, and SR300. Materials and Methods A total of 30 test samples were selected for the test of TSH, ferritin, C-peptide, and insulin serum levels. Test was performed by IRMA method. We compared the difference in the results of applying the linear interpolation method and the spline interpolation method to Gamma Pro, Gamma 10, Cobra, and SR300 equipment. Results Two-way ANOVA was used for statistical analysis. The significance level was applied as P <0.05. The results of TSH, ferritin, C-peptide, and insulin tests were compared between the fully automated radio immunoassay analyzers. There was a significant difference between ferritin, C-peptide, and insulin serum levels(P<0.001). TSH didn't show any significant different between the devices(P=0.29). In the difference between linear and spline interpolation, there was no significant difference between insulin test(P=0.08), TSH test(P=0.81), and Ferritin test(P=0.06). However, C-peptide test showed a significant difference(P=0.03). Especially, the insulin test showed significant difference in lower ranges. As a result of comparing and analyzing the difference between the two interpolation methods, the devices in the low concentration group showed significant difference(P<0.001). Conclusion In case of new equipment in the laboratory it is necessary to recognize that there is a difference in the curve fitting method for each automated radio immunoassay analyzers in the low concentration area when the principle of inspection is IRMA method.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.1
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• pp.16-22
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• 2012

In this paper, we proposed a method of baseline correction for analysis of Raman spectra of platelets from Alzheimer's disease (AD) transgenic mice. Measured Raman spectra include the meaningful information and unnecessary noise which is composed of baseline and additive noise. The Raman spectrum is divided into the local region including several peaks and the spectrum of the region is modeled by curve fitting using Gaussian model. The additive noise is clearly removed from the process of replacing the original spectrum with the fitted model. The baseline correction after interpolating the local minima of the fitted model with linear, piecewise cubic Hermite and cubic spline algorithm. The baseline corrected models extract the feature with principal component analysis (PCA). The classification result of support vector machine (SVM) and maximum $a$ posteriori probability (MAP) using linear interpolation method showed the good performance about overall number of principal components, especially SVM gave the best performance which is about 97.3% true classification average rate in case of piecewise cubic Hermite algorithm and 5 principal components. In addition, it confirmed that the proposed baseline correction method compared with the previous research result could be effectively applied in the analysis of the Raman spectra of platelet.