• Title/Summary/Keyword: F1_Weighted

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PERIOD ANALYSIS FOR THE F COMPONENT OF THE ∈ AURIGAE SYSTEM USING WAVELETS (웨이블렛을 이용한 ∈ AURIGAE SYSTEM 주성 F별의 주기분석)

  • Kim, Hyouk
    • Journal of Astronomy and Space Sciences
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    • v.25 no.1
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    • pp.1-18
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    • 2008
  • We present a detailed period analysis for the F-type primary of ${\in}$ Aurigae by means of Fourier and wavelet algorithm. After collecting all available data which have been observed for around 160 years (1842 - 2006) from various international databases and published references we selected only data obtained during outside eclipse among them again. As a result of analysis using CLEANest and WWZ(weighted wavelet Z-transform) several frequencies including two clear periods ($67^d\;and\;123^d$) were found. In contrast to previous results that the periods vary irregularly it seems that the primary of ${\in}$ Aurigae is double mode or multiperiodic pulsator. The presence of the two periods and their ratio indicates that the high-mass interpretation of the variable could be valid. Also better understanding of the mechanisms driving the light variability of F-type supergiant stars requires continual series of photometric and radial velocity measurements in outside eclipse of this star.

Performance of a Bayesian Design Compared to Some Optimal Designs for Linear Calibration (선형 캘리브레이션에서 베이지안 실험계획과 기존의 최적실험계획과의 효과비교)

  • 김성철
    • The Korean Journal of Applied Statistics
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    • v.10 no.1
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    • pp.69-84
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    • 1997
  • We consider a linear calibration problem, $y_i = $$\alpha + \beta (x_i - x_0) + \epsilon_i$, $i=1, 2, {\cdot}{\cdot},n$ $y_f = \alpha + \beta (x_f - x_0) + \epsilon, $ where we observe $(x_i, y_i)$'s for the controlled calibration experiments and later we make inference about $x_f$ from a new observation $y_f$. The objective of the calibration design problem is to find the optimal design $x = (x_i, \cdots, x_n$ that gives the best estimates for $x_f$. We compare Kim(1989)'s Bayesian design which minimizes the expected value of the posterior variance of $x_f$ and some optimal designs from literature. Kim suggested the Bayesian optimal design based on the analysis of the characteristics of the expected loss function and numerical must be equal to the prior mean and that the sum of squares be as large as possible. The designs to be compared are (1) Buonaccorsi(1986)'s AV optimal design that minimizes the average asymptotic variance of the classical estimators, (2) D-optimal and A-optimal design for the linear regression model that optimize some functions of $M(x) = \sum x_i x_i'$, and (3) Hunter & Lamboy (1981)'s reference design from their paper. In order to compare the designs which are optimal in some sense, we consider two criteria. First, we compare them by the expected posterior variance criterion and secondly, we perform the Monte Carlo simulation to obtain the HPD intervals and compare the lengths of them. If the prior mean of $x_f$ is at the center of the finite design interval, then the Bayesian, AV optimal, D-optimal and A-optimal designs are indentical and they are equally weighted end-point design. However if the prior mean is not at the center, then they are not expected to be identical.In this case, we demonstrate that the almost Bayesian-optimal design was slightly better than the approximate AV optimal design. We also investigate the effects of the prior variance of the parameters and solution for the case when the number of experiments is odd.

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Diffusion-Weighted Imaging for Differentiation of Biliary Atresia and Grading of Hepatic Fibrosis in Infants with Cholestasis

  • Jisoo Kim;Hyun Joo Shin;Haesung Yoon;Seok Joo Han;Hong Koh;Myung-Joon Kim;Mi-Jung Lee
    • Korean Journal of Radiology
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    • v.22 no.2
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    • pp.253-262
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    • 2021
  • Objective: To determine whether the values of hepatic apparent diffusion coefficient (ADC) can differentiate biliary atresia (BA) from non-BA or be correlated with the grade of hepatic fibrosis in infants with cholestasis. Materials and Methods: This retrospective cohort study included infants who received liver MRI examinations to evaluate cholestasis from July 2009 to October 2017. Liver ADC, ADC ratio of liver/spleen, aspartate aminotransferase to platelet ratio index (APRI), and spleen size were compared between the BA and non-BA groups. The diagnostic performances of all parameters for significant fibrosis (F3-4) were obtained by receiver-operating characteristics (ROCs) curve analysis. Results: Altogether, 227 infants (98 males and 129 females, mean age = 57.2 ± 36.3 days) including 125 BA patients were analyzed. The absolute ADC difference between two reviewers was 0.10 mm2/s for both liver and spleen. Liver ADC value was specific (80.4%) and ADC ratio was sensitive (88.0%) for the diagnosis of BA with comparable performance. There were 33 patients with F0, 15 with F1, 71 with F2, 35 with F3, and 11 with F4. All four parameters of APRI (τ = 0.296), spleen size (τ = 0.312), liver ADC (τ = -0.206), and ADC ratio (τ = -0.288) showed significant correlation with fibrosis grade (all, p < 0.001). The cutoff values for significant fibrosis (F3-4) were 0.783 for APRI (area under the ROC curve [AUC], 0.721), 5.9 cm for spleen size (AUC, 0.719), 1.044 x 10-3 mm2/s for liver ADC (AUC, 0.673), and 1.22 for ADC ratio (AUC, 0.651). Conclusion: Liver ADC values and ADC ratio of liver/spleen showed limited additional diagnostic performance for differentiating BA from non-BA and predicting significant hepatic fibrosis in infants with cholestasis.

An 8-bit Data Driving Circuit Design for High-Quality Images in Active Matrix OLEDs (고화질 Active Matrix OLED 디스플레이를 위한 8비트 데이터 구동 회로 설계)

  • Jo, Young-Jik;Lee, Ju-Sang;Yu, Sang-Dae
    • Proceedings of the KIEE Conference
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    • 2004.11c
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    • pp.632-634
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    • 2004
  • First for high-qualify images and reducing process-error and driving speed, the designed 8-bit data driving circuit consists of a constant transconductance bias circuit, D-F/Fs by shift registers using static transmission gates, 1st latch and 2nd latch by tristate inverters, level shifters, current steering segmented D/A converters by 4MSB thermometer decoder and 4LSB weighted type. Second, we designed gray amp for power saving. These data driving circuits are designed with $0.35-{\mu}m$ CMOS technologies at 3.3 V and 18 V power supplies and simulated with HSPICE.

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The Optical Characteristics of High-Brightness LEDs for R/G/B/A/W Properties (고휘도 LED R/G/B/A/W의 광특성)

  • Hwang, Myung-Keun;Song, Jung-Yong;Huh, Chang-Su
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2003.05e
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    • pp.100-103
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    • 2003
  • 고휘도 LED(light emitting diode) 빨강(R), 녹색(G), 파랑(B), 호박색(A), 백색(W) 등의 중요한 광학특성인 광속(luminous flux), 효율(luminous efficacy), 피크 파장(peak wavelength), 가중치 평균 파장(weighted average wavelength), 반치폭 (full width at ha1f maximum), 색도좌표(chromaticity coordinate), 주 파장(dominant wavelength), 자극순도 (excitation purity) 와 휘도순도(colorimetric purity)에 대해서 비교검토하였다. 시험결과로 제시된 LED의 기본적인 특성 데이터는 추후, 새로운 조명용 LED 램프나 등기구(luminaire)를 개발 및 특성연구에 많은 도움을 줄 것으로 사료된다.

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A Korean Named Entity Recognizer using Weighted Voting based Ensemble Technique (가중 투표 기반의 앙상블 기법을 이용한 한국어 개체명 인식기)

  • Kwon, Sunjae;Heo, Yoonseok;Lee, Kyunchul;Lim, Jisu;Choi, Hojeong;Seo, Jungyun
    • 한국어정보학회:학술대회논문집
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    • 2016.10a
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    • pp.333-336
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    • 2016
  • 본 연구에서는 개체명 인식의 성능을 향상시키기 위해, 가중 투표 방법을 이용하여 개체명 인식 모델을 앙상블 하는 방법을 제안한다. 각 모델은 Conditional Random Fields의 변형 알고리즘을 사용하여 학습하고, 모델들의 가중치는 다목적 함수 최적화 기법인 NSGA-II 알고리즘으로 학습한다. 실험 결과 제안 시스템은 $F_1Score$ 기준으로 87.62%의 성능을 보여, 단독 모델 중 가장 높은 성능을 보인 방법보다 2.15%p 성능이 향상되었다.

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Contextualized Embedding- and Character Embedding-based Pointer Network for Korean Coreference Resolution (문맥 표현과 음절 표현 기반 포인터 네트워크를 이용한 한국어 상호참조해결)

  • Park, Cheoneum;Lee, Changki;Ryu, Jihee;Kim, Hyunki
    • Annual Conference on Human and Language Technology
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    • 2018.10a
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    • pp.239-242
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    • 2018
  • 문맥 표현은 Recurrent neural network (RNN)에 기반한 언어 모델을 학습하여 얻은 여러 층의 히든 스테이트(hidden state)를 가중치 합(weighted sum)을 하여 얻어낸 벡터이다. Convolution neural network (CNN)를 이용하여 음절 표현을 학습하는 경우, 데이터 내에서 발생하는 미등록어를 처리할 수 있다. 본 논문에서는 음절 표현 CNN 기반의 포인터 네트워크와 문맥 표현을 함께 이용하는 방법을 제안하고, 이를 상호참조해결에 적용한다. 실험 결과, 질의응답 데이터셋에서 CoNLL F1 57.88%로 규칙기반에 비하여 11.09% 더 좋은 성능을 보였다.

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A Korean Named Entity Recognizer using Weighted Voting based Ensemble Technique (가중 투표 기반의 앙상블 기법을 이용한 한국어 개체명 인식기)

  • Kwon, Sunjae;Heo, Yoonseok;Lee, Kyunchul;Lim, Jisu;Choi, Hojeong;Seo, Jungyun
    • Annual Conference on Human and Language Technology
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    • 2016.10a
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    • pp.333-336
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    • 2016
  • 본 연구에서는 개체명 인식의 성능을 향상시키기 위해, 가중 투표 방법을 이용하여 개체명 인식 모델을 앙상블 하는 방법을 제안한다. 각 모델은 Conditional Random Fields의 변형 알고리즘을 사용하여 학습하고, 모델들의 가중치는 다목적 함수 최적화 기법인 NSGA-II 알고리즘으로 학습한다. 실험 결과 제안 시스템은 $F_1Score$기준으로 87.62%의 성능을 보여, 단독 모델 중 가장 높은 성능을 보인 방법보다 2.15%p 성능이 향상되었다.

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ON THE HAJECK-RENYI-TYPE INEQUALITY FOR $\tilde{\rho}$-MIXING SEQUENCES

  • Choi, Jeong-Yeol;Baek, Jong-Il
    • Honam Mathematical Journal
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    • v.30 no.3
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    • pp.479-486
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    • 2008
  • Let {${\Omega}$, F, P} be a probability space and {$X_n{\mid}n{\geq}1$} be a sequence of random variables defined on it. We study the Hajeck-Renyi-type inequality for p..mixing random variable sequences and obtain the strong law of large numbers by using this inequality. We also consider the strong law of large numbers for weighted sums of ${\tilde{\rho}}$-mixing sequences.

Perceptual weighting on English lexical stress by Korean learners of English

  • Goun Lee
    • Phonetics and Speech Sciences
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    • v.14 no.4
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    • pp.19-24
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    • 2022
  • This study examined which acoustic cue(s) that Korean learners of English give weight to in perceiving English lexical stress. We manipulated segmental and suprasegmental cues in 5 steps in the first and second syllables of an English stress minimal pair "object". A total of 27 subjects (14 native speakers of English and 13 Korean L2 learners) participated in the English stress judgment task. The results revealed that native Korean listeners used the F0 and intensity cues in identifying English stress and weighted vowel quality most strongly, as native English listeners did. These results indicate that Korean learners' experience with these cues in L1 prosody can help them attend to these cues in their L2 perception. However, L2 learners' perceptual attention is not entirely predicted by their linguistic experience with specific acoustic cues in their native language.