• Title/Summary/Keyword: Likelihood ratios

Search Result 91, Processing Time 0.024 seconds

Relation of Conception Rate and Plasma Urea Nitrogen in Dairy Cattle (젖소의 수태율과 혈장 요소태 질소의 관계)

  • 박수봉;김현섭;김창근;정영채;이종완;김천호
    • Korean Journal of Animal Reproduction
    • /
    • v.21 no.2
    • /
    • pp.185-189
    • /
    • 1997
  • The objectives of this study were to relate concentrations of plasma urea nitrogen(PUN) to conception rate in dairy cows. the relationship between PUN concentration and time postcalving was examined for 11 individual cows. Mean concentration of PUN rose for serveral weeks after calving and then was stable from 7 week. As PUN increased, the rate of conception decreased. Cows with PUN<15 and 15∼19.9mg/dl had the likelihood ratios of conception of 1.33 and 1.67. As PUN increased 20∼22.9 and 23mg/dl, the likelihood ratios decreased to 1.00 and 0.90. Thus, low PUN had a favorable association with conception, whereas high PUN had a negative association with conception.

  • PDF

SVM-based Utterance Verification Using Various Confidence Measures (다양한 신뢰도 척도를 이용한 SVM 기반 발화검증 연구)

  • Kwon, Suk-Bong;Kim, Hoi-Rin;Kang, Jeom-Ja;Koo, Myong-Wan;Ryu, Chang-Sun
    • MALSORI
    • /
    • no.60
    • /
    • pp.165-180
    • /
    • 2006
  • In this paper, we present several confidence measures (CM) for speech recognition systems to evaluate the reliability of recognition results. We propose heuristic CMs such as mean log-likelihood score, N-best word log-likelihood ratio, likelihood sequence fluctuation and likelihood ratio testing(LRT)-based CMs using several types of anti-models. Furthermore, we propose new algorithms to add weighting terms on phone-level log-likelihood ratio to merge word-level log-likelihood ratios. These weighting terms are computed from the distance between acoustic models and knowledge-based phoneme classifications. LRT-based CMs show better performance than heuristic CMs excessively, and LRT-based CMs using phonetic information show that the relative reduction in equal error rate ranges between $8{\sim}13%$ compared to the baseline LRT-based CMs. We use the support vector machine to fuse several CMs and improve the performance of utterance verification. From our experiments, we know that selection of CMs with low correlation is more effective than CMs with high correlation.

  • PDF

Joint Performance of Demodulation and Decoding with Regard to Log-Likelihood Ratio Approximation (대수우도비 근사화에 따른 복조와 복호의 결합 성능)

  • Park, Sung-Joon;Jo, Myung-Suk
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.41 no.12
    • /
    • pp.1736-1738
    • /
    • 2016
  • In modern digital communication systems adapting high-order modulation and high performance channel code, log-likelihood ratios involving the repeated calculations of the logarithm of sum of exponential functions are necessary for demodulation and decoding. In this paper, the approximation methods called Min and MinC are applied to demodulation and decoding together and their complexity and joint performance are analyzed.

Utterance Verification using Phone-Level Log-Likelihood Ratio Patterns in Word Spotting Systems (핵심어 인식기에서 단어의 음소레벨 로그 우도 비율의 패턴을 이용한 발화검증 방법)

  • Kim, Chong-Hyon;Kwon, Suk-Bong;Kim, Hoi-Rin
    • Phonetics and Speech Sciences
    • /
    • v.1 no.1
    • /
    • pp.55-62
    • /
    • 2009
  • This paper proposes an improved method to verify a keyword segment that results from a word spotting system. First a baseline word spotting system is implemented. In order to improve performance of the word spotting systems, we use a two-pass structure which consists of a word spotting system and an utterance verification system. Using the basic likelihood ratio test (LRT) based utterance verification system to verify the keywords, there have been certain problems which lead to performance degradation. So, we propose a method which uses phone-level log-likelihood ratios (PLLR) patterns in computing confidence measures for each keyword. The proposed method generates weights according to the PLLR patterns and assigns different weights to each phone in the process of generating confidence measures for the keywords. This proposed method has shown to be more appropriate to word spotting systems and we can achieve improvement in final word spotting accuracy.

  • PDF

Diagnostic Accuracy of Ultrasonograph Guided Fine-needle Aspiration Cytologic in Staging of Axillary Lymph Node Metastasis in Breast Cancer Patients: a Meta-analysis

  • Wang, Xi-Wen;Xiong, Yun-Hui;Zen, Xiao-Qing;Lin, Hai-Bo;Liu, Qing-Yi
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.13 no.11
    • /
    • pp.5517-5523
    • /
    • 2012
  • Purpose: To evaluate the diagnostic accuracy of ultrasonograph and fine-needle aspiration cytologic examination (USG-FNAC) in the staging of axillary lymph node metastasis in breast cancer patients.Methods: We conducted an electronic search of the literature addressing the performance of USG-FNAC in diagnosis of axillary lymph node metastasis in databases such as Pubmed, Medline, Embase, Ovid and Cochrane library. We introduced a series of diagnostic test indices to evaluate the performance of USG-FNAC by the random effect model (REM), including sensitivity, specificity, likelihood ratios, and diagnostic odds ratios and area under the curve (AUC). Results: A total of 20 studies including 1371 cases and 1289 controls were identified. The pooled sensitivity was determined to be 0.66 (95% CI 0.64-0.69), specificity 0.98 (95% CI 0.98-0.99), positive likelihood ratio 22.7 (95% CI 15.0-34.49), negative likelihood ratio 0.32 (95% CI 0.25-0.41), diagnostic OR 84.2 (95% CI 53.3-133.0). Due to the marginal threshold effect found in some indices of diagnostic validity, we used a summary SROC curve to aggregate data, and obtained a symmetrical curve with an AUC of 0.942. Conclusion: The results of this meta-analysis indicated that the USG-FNAC techniques have acceptable diagnostic validity indices and can be used for early staging of axillary lymph node in breast cancer patients.

Meta-analysis of Associations of the Ezrin Gene with Human Osteosarcoma Response to Chemotherapy and Prognosis

  • Wang, Zhe;He, Mao-Lin;Zhao, Jin-Min;Qing, Hai-Hui;Wu, Yang
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.14 no.5
    • /
    • pp.2753-2758
    • /
    • 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.

Estimation and Prediction-Based Connection Admission Control in Broadband Satellite Systems

  • Jang, Yeong-Min
    • ETRI Journal
    • /
    • v.22 no.4
    • /
    • pp.40-50
    • /
    • 2000
  • We apply a "sliding-window" Maximum Likelihood(ML) estimator to estimate traffic parameters On-Off source and develop a method for estimating stochastic predicted individual cell arrival rates. Based on these results, we propose a simple Connection Admission Control(CAC)scheme for delay sensitive services in broadband onboard packet switching satellite systems. The algorithms are motivated by the limited onboard satellite buffer, the large propagation delay, and low computational capabilities inherent in satellite communication systems. We develop an algorithm using the predicted individual cell loss ratio instead of using steady state cell loss ratios. We demonstrate the CAC benefits of this approach over using steady state cell loss ratios as well as predicted total cell loss ratios. We also derive the predictive saturation probability and the predictive cell loss ratio and use them to control the total number of connections. Predictive congestion control mechanisms allow a satellite network to operate in the optimum region of low delay and high throughput. This is different from the traditional reactive congestion control mechanism that allows the network to recover from the congested state. Numerical and simulation results obtained suggest that the proposed predictive scheme is a promising approach for real time CAC.

  • PDF

Discriminative Weight Training for a Statistical Model-Based Voice Activity Detection (통계적 모델 기반의 음성 검출기를 위한 변별적 가중치 학습)

  • Kang, Sang-Ick;Jo, Q-Haing;Park, Seung-Seop;Chang, Joon-Hyuk
    • The Journal of the Acoustical Society of Korea
    • /
    • v.26 no.5
    • /
    • pp.194-198
    • /
    • 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.

Statistical Model-Based Voice Activity Detection Using the Second-Order Conditional Maximum a Posteriori Criterion with Adapted Threshold (적응형 문턱값을 가지는 2차 조건 사후 최대 확률을 이용한 통계적 모델 기반의 음성 검출기)

  • Kim, Sang-Kyun;Chang, Joon-Hyuk
    • The Journal of the Acoustical Society of Korea
    • /
    • v.29 no.1
    • /
    • pp.76-81
    • /
    • 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.

Voice Activity Detection Based on Discriminative Weight Training with Feedback (궤환구조를 가지는 변별적 가중치 학습에 기반한 음성검출기)

  • Kang, Sang-Ick;Chang, Joon-Hyuk
    • The Journal of the Acoustical Society of Korea
    • /
    • v.27 no.8
    • /
    • pp.443-449
    • /
    • 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.