• 제목/요약/키워드: statistical activity

검색결과 1,462건 처리시간 0.031초

Multivariate statistical analysis of the comparative antioxidant activity of the total phenolics and tannins in the water and ethanol extracts of dried goji berry (Lycium chinense) fruits

  • Kim, Joo-Shin;Kimm, Haklin Alex
    • 한국식품과학회지
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    • 제51권3호
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    • pp.227-236
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    • 2019
  • Antioxidant activity in water and ethanol extracts of dried Lycium chinense fruit, as a result of the total phenolic and tannin content, was measured using a number of chemical and biochemical assays for radical scavenging and inhibition of lipid peroxidation, with the analysis being extended by applying a bootstrapping statistical method. Previous statistical analyses mostly provided linear correlation and regression analyses between antioxidant activity and increasing concentrations of phenolics and tannins in a concentration-dependent mode. The present study showed that multiple component or multivariate analysis by applying multiple regression analysis or regression planes proved more informative than linear regression analysis of the relationship between the concentration of individual components and antioxidant activity. In this paper, we represented the multivariate analysis of antioxidant activities of both phenolic and tannin contents combined in the water and ethanol extracts, which revealed the hidden observations that were not evident from linear statistical analysis.

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

  • 김상균;장준혁
    • 한국음향학회지
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    • 제29권1호
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    • pp.76-81
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    • 2010
  • 본 논문에서는 음성의 통계적 모델에 기반한 음성 검출기 (voice activity detection, VAD)의 성능 향상을 위해 2차 조건 사후 최대 확률 (second-order conditional maximum a posteriori, second-order CMAP)기법을 적용한 우도비 테스트 (likelihood ratio test, LRT)를 제안한다. 제안된 알고리즘은, 기존의 통계적 모델에 기반한 음성 검출기와 CMAP 기반의 음성 검출기를 분석한 다음, 직전 2 프레임에서 음성의 존재와 부재에 대한 조건부 확률에 따라 실시간으로 적응형 문턱값을 구하여 기하 평균한 우도비와 비교하는 음성검출 결정법 (decision rule)을 제시한다. 제안된 알고리즘을 비정상 (non-stationary) 잡음환경에서 기존의 통계적 모델에 기반한 음성 검출기, CMAP 기반의 음성 검출기와 비교하였으며, 향상된 성능을 보였다.

An Incremental Statistical Method for Daily Activity Pattern Extraction and User Intention Inference

  • Choi, Eu-Ri;Nam, Yun-Young;Kim, Bo-Ra;Cho, We-Duke
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제3권3호
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    • pp.219-234
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    • 2009
  • This paper presents a novel approach for extracting simultaneously human daily activity patterns and discovering the temporal relations of these activity patterns. It is necessary to resolve the services conflict and to satisfy a user who wants to use multiple services. To extract the simultaneous activity patterns, context has been collected from physical sensors and electronic devices. In addition, a context model is organized by the proposed incremental statistical method to determine conflicts and to infer user intentions through analyzing the daily human activity patterns. The context model is represented by the sets of the simultaneous activity patterns and the temporal relations between the sets. To evaluate the method, experiments are carried out on a test-bed called the Ubiquitous Smart Space. Furthermore, the user-intention simulator based on the simultaneous activity patterns and the temporal relations from the results of the inferred intention is demonstrated.

인진사령산(茵陳四岺散)과 소시호탕(小柴胡湯)이 ANIT 로 유발(誘發)된 담즙울체성(膽汁鬱滯性) 간장애(肝障碍)에 미치는 영향(影響) (Experimental Study of the Effect of Injinsaryungsan and Sosihotang on cholestatic liver injury induced by $ANIT({\alpha}-naphtylisothiocyanate)$)

  • 신상만;이장훈;우홍정
    • 대한한의학회지
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    • 제17권2호
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    • pp.214-226
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    • 1996
  • In an attempt to evaluate the effect of high and low concentration of Injinsaryungsan and high and low concentration of Sosihotang on cholestatic liver injery induced by $ANIT({\alpha}-naphthylisothiocyanate)$, biochemical changes in serum transaminase(GOT, GPT), alkaline phosphate, lactate dehydrogenase, total cholesterol, triglyceride, total-bilirubine were studied and the following results were obtained. 1. High concentration of Injinsaryungsan(2.2g/Kg) inhibited significantly the activity increases of GOT, GPT, ALP, LDH, TC, TG, T-Bilirubine induced by $ANIT({\alpha}-naphthylisothiocyanate)$. 2. Low concentration of Injinsaryungsan(1.1g/Kg) inhibited the activity increases of ALP, LDH, TC, TG with statistical significance, while inhibited the activity increase of GOT ,but with no statistical significance. 3. High concentration of Sosihotang(2.4g/Kg) inhibited the activity increases of LDH, TG, TC with statistical significance while inhibited the activity increases of GOT, GPT, ALP, T-bilirubine with no significance. 4. Low concentration of Sosihotang(1.2g/Kg) inhibited the activity increase of TG, while inhibited the activity increase of ALP, TC with no statistical sig-nificance, but didn't inhibite the activity increases of GOT, GPT, LDH, T-Bil. These results suggest that Injinsaryungsan has more significant effect on the liver injury induced by $ANIT({\alpha}-naphthylisothiocyanate)$ compared with Sosihotang and so can be applicable clinically to virus hepatitis and cholestatic liver injury. Further study will be required to evaluate the effect of Sosibotang on cholangitis and cholecystitis.

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Statistical Model-Based Voice Activity Detection Based on Second-Order Conditional MAP with Soft Decision

  • Chang, Joon-Hyuk
    • ETRI Journal
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    • 제34권2호
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    • pp.184-189
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    • 2012
  • In this paper, we propose a novel approach to statistical model-based voice activity detection (VAD) that incorporates a second-order conditional maximum a posteriori (CMAP) criterion. As a technical improvement for the first-order CMAP criterion in [1], we consider both the current observation and the voice activity decision in the previous two frames to take full consideration of the interframe correlation of voice activity. This is clearly different from the previous approach [1] in that we employ the voice activity decisions in the second-order (previous two frames) CMAP, which has quadruple thresholds with an additional degree of freedom, rather than the first-order (previous single frame). Also, a soft-decision scheme is incorporated, resulting in time-varying thresholds for further performance improvement. Experimental results show that the proposed algorithm outperforms the conventional CMAP-based VAD technique under various experimental conditions.

Bioprocess Development for Production of Alkaline Protease by Bacillus pseudofirmus Mn6 Through Statistical Experimental Designs

  • Abdel-Fattah, Y.R.;El-Enshasy, H.A.;Soliman, N.A.;El-Gendi, H.
    • Journal of Microbiology and Biotechnology
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    • 제19권4호
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    • pp.378-386
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    • 2009
  • A sequential optimization strategy, based on statistical experimental designs, is employed to enhance the production of alkaline protease by a Bacillus pseudofirmus local isolate. To screen the bioprocess parameters significantly influencing the alkaline protease activity, a 2-level Plackett-Burman design was applied. Among 15 variables tested, the pH, peptone, and incubation time were selected based on their high positive significant effect on the protease activity. A near-optimum medium formulation was then obtained that increased the protease yield by more than 5-fold. Thereafter, the response surface methodology(RSM) was adopted to acquire the best process conditions among the selected variables, where a 3-level Box-Behnken design was utilized to create a polynomial quadratic model correlating the relationship between the three variables and the protease activity. The optimal combination of the major medium constituents for alkaline protease production, evaluated using the nonlinear optimization algorithm of EXCEL-Solver, was as follows: pH of 9.5, 2% peptone, and incubation time of 60 h. The predicted optimum alkaline protease activity was 3,213 U/ml/min, which was 6.4 times the activity with the basal medium.

조건 사후 최대 확률과 음성 스펙트럼 변이 조건을 이용한 통계적 모델 기반의 음성 검출기 (A Statistical Model-Based Voice Activity Detection Employing the Conditional MAP Criterion with Spectral Deviation)

  • 김상균;장준혁
    • 한국음향학회지
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    • 제30권6호
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    • pp.324-329
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    • 2011
  • 본 논문에서는 조건 사후 최대 확률 (conditional maximum a posteriori, CMAP)과 음성 스펙트럼 변이 조건을 기반으로 한 새로운 음성 검출기 (voice activity detection, VAD)를 제안한다. 제안된 음성 검출기는 통계적 모델을 기반으로 한 우도비 테스트 (likelihood ratio test, LRT)의 문턱값을 결정하는데 조건 사후 최대 확률과 스펙트럼 변이의 상태 값을 조건부 확률로 부과한다. 제안된 알고리즘을 다양한 잡음 환경에서 기존의 CMAP 기반의 음성 검출기와 비교한 결과 전체적으로 향상된 성능을 보였으며 특히 SNR이 낮은 조건에서 향상 폭이 컸다.

표집 시뮬레이션을 활용한 비형식적 통계적 추리의 교수-학습: 문화-역사적 활동이론의 관점에 따른 분석 (Teaching and learning about informal statistical inference using sampling simulation : A cultural-historical activity theory analysis)

  • 서민주;서유민;정혜윤;이경화
    • 한국학교수학회논문집
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    • 제26권1호
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    • pp.21-47
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    • 2023
  • 본 연구에서는 문화-역사적 활동이론에 기반하여, 표집 시뮬레이션을 활용한 비형식적 통계적 추리의 교수-학습 과정을 활동체계로 고려하고, 이러한 활동체계에서 발생하는 모순과 모순에 의한 변화를 확인하고자 하였다. 이를 위해 초등학생 5~6학년 20명을 대상으로 표집 시뮬레이션을 활용한 비형식적 통계적 추리에 대한 수업을 진행하고 활동체계를 분석하였다. 주제분석을 수행한 결과는 다음과 같다. 먼저, 규칙과 목표, 인공물과 목표 사이의 모순이 발생했으며, 이를 해결하는 과정에서 경험적 표집 분포의 시각화라는 새로운 인공물이 도입되는 것을 확인할 수 있었다. 또한, 규칙과 인공물, 규칙과 주체 사이의 모순이 발생했으며, 이를 해결하는 과정에서 표본 평균들의 평균을 구하는 알고리즘이 새로운 규칙으로 도입되는 것을 확인할 수 있었다.

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

  • 강상익;조규행;박승섭;장준혁
    • 한국음향학회지
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    • 제26권5호
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    • pp.194-198
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    • 2007
  • 본 논문에서는 음성의 통계적 모델에 기반한 음성검출기의 성능향상을 위해 변별적 가중치 학습(discriminative weight training) 기반의 최적화된 우도비 테스트(Likelihood Ratio Test, LRT)를 제안한다. 먼저, 기존의 통계모델기반의 음성검출기를 분석하고, 이를 기반으로 MCE(minimum classification error)방법을 도입하여, 각 주파수 채널별로 다른 가중치를 가지는 우도비 기반의 음성검출 결정법(decision rule)을 제시한다. 제안된 알고리즘은 비정상(non-stationary)잡음환경에서 기존의 동일 가중치를 가지는 기하 평균 기반의 음성검출기와 비교하였으며, 우수한 성능을 보인다.

통계 및 프리커서 방법을 이용한 제23주기 태양활동예보 (PREDICTION OF 23RD SOLAR CYCLE USING THE STATISTICAL AND PRECURSOR METHOD)

  • 장세진;김갑성
    • 천문학논총
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    • 제14권2호
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    • pp.91-102
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    • 1999
  • We have made intensive calculations on the maximum relative sunspot number and the date of solar maximum of 23rd solar cycle, by using the statistical and precursor methods to predict solar activity cycle. According to our results of solar data processing by statistical method, solar maximum comes at between February and July of 2000 year and at that time, the smoothed sunspot number will reach to $114.3\~122.8$. while precursor method gives rather dispersed value of $118\~17$ maximum sunspot number. It is found that prediction by statistical method using smoothed relative sunspot number is more accurate than by any method to use any data of 10.7cm radio fluxes and geomagnetic aa, Ap indexes, from the full analysis of solar cycle pattern of these data. In fact, current ascending pattern of 23rd solar cycle supports positively our predicted values. Predicted results by precursor method for $Ap_{avg},\;aa_{31-36}$ indexes show similar values to those by statistical method. Therefore, these indexes can be used as new precursors for the prediction of 23rd or next solar cycle.

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