• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.97-110
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• 2006

Since it is well-established that even high quality data tend to contain outliers, one would expect fat? greater reliance on robust regression techniques than is actually observed. But most of all robust regression estimators suffers from the computational difficulties and the lower efficiency than the least squares under the normal error model. The weighted self-tuning estimator (WSTE) recently suggested by Lee (2004) has no more computational difficulty and it has the asymptotic normality and the high break-down point simultaneously. Although it has better properties than the other robust estimators, WSTE does not have full efficiency under the normal error model through the weighted least squares which is widely used. This paper introduces a new approach as called the reweighted WSTE (RWSTE), whose scale estimator is adaptively estimated by the self-tuning constant. A Monte Carlo study shows that new approach has better behavior than the general weighted least squares method under the normal model and the large data.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.537-549
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• 1995

In this article, we propose a class of weighted estimators for the excess risk in additive risk model with a binary covariate. The proposed estimator is consistent and asymptotically normal. When the assumed model is inappropriate, however, the estimators with different weights converge to nonidentical constants. This fact enables us to develop a goodness-of-fit test for the excess assumption by comparing estimators with diffrent weights. It is shown that the proposed test converges in distribution to normal with mean zero and is consistent under the model misspecifications. Furthermore, the finite-sample properties of the proposed test procedure are investigated and two examples using real data are presented.

• Korean Journal of Veterinary Research
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• v.44 no.2
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• pp.311-315
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• 2004

The detection of lymph node metastasis is an important step in tumor staging and is significant for therapy planning. It has been challenged to yield an appropriate image with diagnostic methods such as Magnetic Resonance (MR) and Computed Tomography (CT). Though CT has been used widely and accessed easily to show internal organs, it can hardly provide difference between lymph node and adjacent vessel or fat tissue. It has been well established that MR can reveal the subtle discrepancy within soft tissue. This study investigated the suitability of MR lymph node imaging without contrast enhancement by comparison of T1-weighted image (T1WI) and T2- weighted image (T2WI) in ten normal rabbits. According to the pulse sequence optimized from preliminary study, T1-weighted spin-echo (repetition time/echo time=400/12 ms) and T-2 weighted fast spin-echo (repetition time/echo time=3500/84 ms) images covering the hind limbs and pelvic region were acquired at 1.5 T. Two radiologists scrupulously evaluated the MR images in consensus. And signal intensity of lymph nodes was compared with that of adjacent fat. Statistical analysis showed that T1-weighted coronal image visualized the lymph nodes (iliac, superficial inguinal and popliteal lymph nodes) quickly and consistently rather than T2-weighted one. Conclusively, T1WI for evaluation of lymph nodes is moderately better than T2WI and appears to have potential for quick and sufficient mapping of the lymph nodes. In addition, this normal MR image of lymph nodes could be applied to further study for the evaluation of lymphatic system in abscess and tumor bearing animal model.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.57.2-57.2
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• 2014

Protostellar jets and outflows are signatures of star formation and promising mechanisms for driving supersonic turbulence in molecular clouds. We quantify outflow-driven turbulence through three-dimensional numerical simulations using an isothermal version of the total variation diminishing code. We drive turbulence in real space using a simplified spherical outflow model, analyze the data through density probability distribution functions (PDFs), and investigate density and velocity power spectra. The real-space turbulence-driving method produces a negatively skewed density PDF possessing an enhanced tail on the low-density side. It deviates from the log-normal distributions typically obtained from Fourier-space turbulence driving at low densities, but can provide a good fit at high densities, particularly in terms of mass-weighted rather than volume-weighted density PDF. We find shallow density power-spectra of -1.2. It is attributed to spherical shocks of outflows themselves or shocks formed by the interaction of outflows. The total velocity power-spectrum is found to be -2.0, representative of the shock dominated Burger's turbulence model. Our density weighted velocity power spectrum is measured as -1.6, slightly less that the Kolmogorov scaling values found in previous works.

• Journal of radiological science and technology
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• v.24 no.2
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• pp.19-22
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• 2001

The purpose of this study is to evaluate time course of signal enhancement on Gadomer-17 enhance MRI, and to correlate the size of enhanced area with that of the infarct area on 2'3'5'-triphenyl tetrazolium chloride(TTC) histochemical examination for the assessment of myocardial viability in reperfused Myocardial Infarction in a cat model. Tan cats(average weight: 3.8 kg) which had undergone 90 minutes of occlusion of the LAD followed by 90 minutes of reperfusion underwent MR T2-weighted imaging, and T1-weighted imaging, enhanced T1-weighted imaging. We used 1.5T Magneton Vision MRI system(Siemens, Erlangen, Germany). Signal intensities were measured in the enhanced and non-enhanced areas of enhanced T1-weighted imaging. and TTC histochemical staining the size of the abnormal signal area on each image was compared with that of the infarct area. Maximum enhancement was detected during a $40{\sim}60$ minute period with an average enhancement of $168{\pm}9.9%$ of normal myocardium. TTC staining revealed that the size of the high signal area on T2-weighted images and of the enhanced area on enhanced T1-weighted images was greater than that of the infarct area($T2=48.1%{\pm}3.7$, enhanced $T1=47.2%{\pm}2.6$, TTC $staining=38.7%{\pm}3.1$ ; p<0.05). In reperfused Myocardial Infarction in a cat model, enhanced MR imaging delineates reversibly and irreversibly damaged myocardium, with a strong enhancement and a broad temporal window. We may therefore expect that enhanced MR image is useful for demonstrating myocardial injury.

• Biomedical Science Letters
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• v.10 no.3
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• pp.285-291
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• 2004

To determine the magnetic resonance (MR) imaging findings and natural history of cerebral fat embolism in a cat model, and to correlate the MR imaging and histologic fmdings. Intemel carotid artery of 11 cats was injected with 0.1 ml of triolein. T2-weighted, T1-weighted and Gd-enhanced T1-weighted images were obtained serially for 2 hours, 1 days, 4 days, 1 week, 2 weeks and 3 weeks after embolization. Any abnormal signal intensity was evaluated. After MR imaging at 3 weeks, brain tissue was obtained for light microscopic (LM) examination using hematoxylin-eosin (HE) and Luxol fast blue staining, and for electron microscopic examination. The LM examination with HE staining revealed normal histological findings in the greater part of an embolized lesion. Cystic change was observed in the gray matter of 8 cats, while in the gray and white matter of 3 cats. At LM examination, Luxol fast blue, staining demonstrated demyelination around the cystic change occurring in the white matter, and EM examination of the embolized cortex revealed sporadic intracapillary fat vacuoles (n=11) and disruption of the blood-brain barrier (n=4). Most lesions were normal, however, and perivascular interstitial edema and cellular swelling were mild compared with the control side. The greater part of an embolized lesion showed reversible findings at MR and histological examination. Irreversible focal necrosis was, however, observed in gray and white matter at weeks 3.

• Investigative Magnetic Resonance Imaging
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• v.21 no.2
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• pp.65-70
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• 2017

Purpose: To optimize the saturation time and maximizing the pH-weighted difference between the normal and ischemic brain regions, on 3-tesla amide proton transfer (APT) imaging using an in vivo rat model. Materials and Methods: Three male Wistar rats underwent middle cerebral artery occlusion, and were examined in a 3-tesla magnetic resonance imaging (MRI) scanner. APT imaging acquisition was performed with 3-dimensional turbo spin-echo imaging, using a 32-channel head coil and 2-channel parallel radiofrequency transmission. An off-resonance radiofrequency pulse was applied with a Sinc-Gauss pulse at a $B_{1,rms}$ amplitude of $1.2{\mu}T$ using a 2-channel parallel transmission. Saturation times of 3, 4, or 5 s were tested. The APT effect was quantified using the magnetization-transfer-ratio asymmetry at 3.5 ppm with respect to the water resonance (APT-weighted signal), and compared with the normal and ischemic regions. The result was then applied to an acute stroke patient to evaluate feasibility. Results: Visual detection of ischemic regions was achieved with the 3-, 4-, and 5-s protocols. Among the different saturation times at $1.2{\mu}T$ power, 4 s showed the maximum difference between the ischemic and normal regions (-0.95%, P = 0.029). The APTw signal difference for 3 and 5 s was -0.9% and -0.7%, respectively. The 4-s saturation time protocol also successfully depicted the pH-weighted differences in an acute stroke patient. Conclusion: For 3-tesla turbo spin-echo APT imaging, the maximal pH-weighted difference achieved when using the $1.2{\mu}T$ power, was with the 4 s saturation time. This protocol will be helpful to depict pH-weighted difference in stroke patients in clinical settings.

• Journal of Internet Computing and Services
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• v.15 no.3
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• pp.109-116
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• 2014

This study proposed new instance selection using neural network with weighted fuzzy membership functions(NEWFM) based on Takagi-Sugeno(T-S) fuzzy model to improve the classification performance. The proposed instance selection adopted weighted average defuzzification of the T-S fuzzy model and an interval selection, same as the confidence interval in a normal distribution used in statistics. In order to evaluate the classification performance of the proposed instance selection, the results were compared with depending on whether to use instance selection from the case study. The classification performances of depending on whether to use instance selection show 77.33% and 78.19%, respectively. Also, to show the difference between the classification performance of depending on whether to use instance selection, a statistics methodology, McNemar test, was used. The test results showed that the instance selection was superior to no instance selection as the significance level was lower than 0.05.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.1-13
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• 2021

Previous studies have found the significant adverse effects of coronavirus disease 2019 (COVID-19) on stock returns and volatility. The effects varied with the confirmed cases and deaths. However, the extent of the effects have never been measured exactly. This study proposes a measurement model for the COVID-19 effects. In the proposed model, stock returns in the COVID-19 period are weighted averages of pre-COVID-19 normal returns and COVID-19-induced returns. The effects are measured by the contributing weights of the COVID-19-induced returns. Kalman filtering is used to estimate the model for the world and Chinese markets, in combination with 10 markets - five most affected countries (United States, India, Brazil, Russia, and France) and five best recovering countries (Hong Kong, Australia, Singapore, Thailand, and South Korea). The sample returns are daily, obtained from the closing Morgan Stanley global investable market indexes. The full period is from September 24, 2018, to October 30, 2020, whereas the COVID-19 period is from November 18, 2019, to October 30, 2020. The contributing weights are significant and close to 100% for all markets. The COVID-19-induced returns replace the pre-COVID-19 normal returns; they are negatively auto-correlated and highly volatile. The COVID-19-induced returns are new normal returns in the COVID-19 period.

• Investigative Magnetic Resonance Imaging
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• v.6 no.2
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• pp.158-165
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• 2002

Purpose : To evaluate the effect of Gd-DTPA on signal intensity of diffusion-weighted magnetic resonance(MR) image and apparent diffuse coefficient (ADC) in dog brain with hype racute stroke. Materials and methods : Experimental canine model of hyperacute cerebral infarction was made by selective intraarterial embolization with particulate embolic material. Diffusion-weighted MR imaging was performed in five dogs at 1 hour after the embolization of internal carotid artery. After intravenous bolus injection of Gd- DTPA, additional 11 diffusion-weighted MR images were serially obtained from 2 minutes to 90 minutes after injection in each dog. The author evaluated findings of hyperacute cerebral infarction on diffusion-weighted MR imaging, and calculated mean signal intensity and mean ADC in infarcted region and contralateral normal region. Statistical analysis of mean signal intensity, mean ADC and contrast-noise ratio before and after Gd-DTPA injection was performed. Results : Hyperacute cerebral infarction developed in all five dogs on diffusion-weighted MR images obtained 1 hour after embolization. The area of hyperacute infarction had steady increase in signal intensity on diffusion-weighted MR image and decrease in ADC. In normal perfusion area, decrease in signal intensity was observed at 2 minutes the Gd-DTPA injection, whereas ADC did not changed. Conclusion : Intravenous injection of Gd-DTPA had no influence on ADC in both hyperacute infarction and normally perfused are a, but caused initial transient signal reduction in normally perfused area on diffusion-weighted MR image due to susceptibility effect of Gd-DTPA. It is important to calculate ADC in evaluating the effect of diffusion after injection of Gd-DTPA.