• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.2C
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• pp.117-122
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• 2006

In this paper, we present a simple and general soft bit decision expression for a Gray coded PAM signal over additive white Gaussian noise(AWGN) channel with the log likelihood ratio(LLR). In order to reduce the complexity of the LLR calculation, we make the bitwise LLR expression simple by replacing the mathematical max functions of the conventional Max-Log-MAP expression with simple arithmetic functions associated with some deterministic parameters, such as a received value and distance between symbols on a signal space. Taking the implementation issues, like the area of silicon, the power consumption, the timing latency, and so on, into consideration, we submit that the proposed method is a promising alternative way to conventional methods for reconfigurable systems.

• 대한예방의학회:학술대회논문집
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• 1994.02b
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• pp.164-168
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• 1994

Single serologic tests may occasionally influence clinicians in making diagnoses. The antistreptolysin O (ASO) test is a frequently used tool for detecting recent Streptococcus pyogenes infection and is helpful in the diagnosis of diseases like rheumatic fever. Using data from a 1989 prospective study of 600 healthy male military recruits, in which 43% experienced S. pyogenes upper respiratory tract infection (2-dilution rise in ASO), this report compared two methods of interpreting a single ASO titer. Using the 'upper limit of normal' (80 percentile) method, recruits with an ASO titer of greater than 400 showed evidence of recent S. pyogenes infection. This method had a sensitivity and specificity of only 65.9 and 81.9% respectively. In contrast to the 'yes-no'. dichotomy of the 'upper limit of normal' method. the likelihood ratio method statistics were ASO value specific, more consistent with clinical judgment, and better emphasized the caution clinicians must use in interpreting a single ASO test.

• The Journal of the Acoustical Society of Korea
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• v.26 no.5
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• pp.194-198
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• 2007

In this paper, we apply a discriminative weight training to a statistical model-based voice activity detection(VAD). In our approach, the VAD decision rule is expressed as the geometric mean of optimally weighted likelihood ratios(LRs) based on a minimum classification error(MCE) method which is different from the previous works in that different weights are assigned to each frequency bin which is considered more realistic. According to the experimental results, the proposed approach is found to be effective for the statistical model-based VAD using the LR test.

• The Journal of the Acoustical Society of Korea
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• v.29 no.1
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• pp.76-81
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• 2010

In this paper, we propose a novel approach to improve the performance of a statistical model-based voice activity detection (VAD) which is based on the second-order conditional maximum a posteriori (CMAP). In our approach, the VAD decision rule is expressed as the geometric mean of likelihood ratios (LRs) based on adapted threshold according to the speech presence probability conditioned on both the current observation and the speech activity decisions in the pervious two frames. Experimental results show that the proposed approach yields better results compared to the statistical model-based and the CMAP-based VAD using the LR test.

• The Journal of the Acoustical Society of Korea
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• v.27 no.8
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• pp.443-449
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• 2008

One of the key issues in practical speech processing is to achieve robust Voice Activity Deteciton (VAD) against the background noise. Most of the statistical model-based approaches have tried to employ equally weighted likelihood ratios (LRs), which, however, deviates from the real observation. Furthermore voice activities in the adjacent frames have strong correlation. In other words, the current frame is highly correlated with previous frame. In this paper, we propose the effective VAD approach based on a minimum classification error (MCE) method which is different from the previous works in that different weights are assigned to both the likelihood ratio on the current frame and the decision statistics of the previous frame.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.2753-2758
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• 2013

Various studies examining the relationship between Ezrin overexpression and response to chemotherapy and clinical outcome in patients with osteosarcoma have yielded inconclusive results. We accordingly conducted a meta-analysis of 7 studies (n = 318 patients) that evaluated the correlation between Ezrin and histologic response to chemotherapy and clinical prognosis (death). Data were synthesized in receiver operating characteristic curves and with fixed-effects and random-effects likelihood ratios and risk ratios. Quantitative synthesis showed that Ezrin is not a prognostic factor for the response to chemotherapy. The positive likelihood ratio was 0.538 (95% confidence interval [95% CI], 0.296- 0.979; random-effects calculation), and the negative likelihood ratio was 2.151 (95% CI, 0.905- 5.114; random-effects calculations). There was some between-study heterogeneity, but no study showed strong discriminating ability. Conversely, Ezrin positive status tended to be associated with a lower 2-year survival (risk ratio, 2.45; 95% CI, 1.26-4.76; random-effects calculation) with some between-study heterogeneity that disappeared when only studies that employed immunohistochemistry were considered (risk ratio, 2.97; 95% CI, 2.01- 4.40; fixed-effects calculation). To conclude, Ezrin is not associated with the histologic response to chemotherapy in patients with osteosarcoma, whereas Ezrin positivity was associated with a lower 2-year survival rate regarding risk of death at 2 years. Expression change of Ezrin is an independent prognostic factor in patients with osteosarcoma.

• The Journal of the Acoustical Society of Korea
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• v.24 no.3
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• pp.150-159
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• 2005

This paper addresses a voice personality transformation algorithm which makes one person's voices sound as if another person's voices. In the proposed method, one person's voices are represented by LPC cepstrum, pitch period and speaking rate, the appropriate transformation rules for each Parameter are constructed. The Gaussian Mixture Model (GMM) is used to model one speaker's LPC cepstrums and conditional probability is used to model the relationship between two speaker's LPC cepstrums. To obtain the parameters representing each probabilistic model. a Maximum Likelihood (ML) estimation method is employed. The transformed LPC cepstrums are obtained by using a Minimum Mean Square Error (MMSE) criterion. Pitch period and speaking rate are used as the parameters for prosody transformation, which is implemented by using the ratio of the average values. The proposed method reveals the superior performance to the previous VQ-based method in subjective measures including average cepstrum distance reduction ratio and likelihood increasing ratio. In subjective test. we obtained almost the same correct identification ratio as the previous method and we also confirmed that high qualify transformed speech is obtained, which is due to the smoothly evolving spectral contours over time.

• Journal of the Korean Statistical Society
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• v.12 no.1
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• pp.24-35
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• 1983

In fitting models to data, selection of the most desirable estimation method and determination of the adequacy of fitted model are the central issues. This paper compares the maximum likelihood estimators and the minimum logit chi-square estimators, both being best asymptotically normal, when logit models are fitted to infant mortality data. Chi-square goodness-of-fit test and likelihood ratio one are also compared. The analysis infant mortality data shows that the outlying observations do not necessarily result in the same impact on goodness-of-fit measures.

• Journal of the Korean Statistical Society
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• v.25 no.4
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• pp.489-497
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• 1996

Lower bounds for the full level probabilities are derived under order restrictions in weights. Discussions are made on typical isotonic cones such as linear order, simple tree order, and unimodal order cones. We also discuss applications of these results for constructing conditional likelihood ratio tests for ordered hypotheses in a contingency table. A real data set on torus mandibularis will be analyzed for illustrating the testing procedure.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.511-518
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• 2009

We consider the problem of testing for change and estimating the unknown change-point in a sequence of time-ordered observations from the binomial and Poisson distributions. Including the likelihood ratio test, Gombay and Horvath (1990) tests are studied and the proposed change-point estimator is derived from their test statistic. A power study of tests and a comparison study of change-point estimators are done via simulation.