• 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.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.8-8
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• 2018

전통적인 빈도해석은 정상성 가정을 기초로 단일 확률분포를 강우 및 홍수량 자료에 적용하는 과정을 통해 확률수문량을 추정하는 것을 목적으로 하고 있다. 그러나 전지구적인 기상학적 변동성 및 기후변화로 기인하는 극치수문량의 발생 빈도 및 양적 크기의 변화는 확률통계학적 관점에서 서로 다른 분포특성을 가지게 된다. 대표적인 기상변동성인 엘니뇨가 발생하는 경우 지역에 따라 홍수 및 가뭄이 발생 발생하게 되며, 이러한 극치수문량은 일반적으로 나타나는 홍수 및 가뭄의 분포특성과는 상이한 경우가 많다. 즉, 2개 이상의 확률분포 특성이 혼재된 혼합분포의 특성을 가지는 경우가 나타내게 되며 이를 고려한 빈도해석 기법의 개발 및 적용이 필요하다. 혼합분포를 활용한 빈도해석에서 가장 중요한 사항 중에 하나는 개별 분포에 적용되는 가중치를 추정하는 것으로서 통계학적 관점에서 자료의 특성에 근거하여 내재되어 있는 은닉상태(latent process)를 추정하는 과정과 유사하다. 이와 더불어 앞서 언급된 기상학적 변동성을 빈도해석에 반영하기 위한 비정상성 해석기법의 개발 및 적용도 필요하다. 본 연구에서는 혼합분포를 활용한 비정상성빈도해석모형을 개발하는데 목적이 있으며 개별매개변수의 동적거동 뿐만 아니라 가중치에 대한 시간적인 종속성도 고려할 수 있는 모형으로 동적모형으로 다양한 실험적 해석이 가능하다. 본 연구에서는 개발된 모형을 기반으로 엘니뇨와 같은 기상변동성에 따른 강우 및 홍수빈도해석 측면에서 은닉상태에 변화, 이로 인한 확률분포의 특성 및 설계수문량의 동적변동성을 평가하고자 한다.

• Composites Research
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• v.37 no.3
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• pp.179-185
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• 2024

This study quantitatively evaluated and investigated the changes in transverse tensile strength of unidirectional fiber-reinforced composites with initial void defects using a Representative Volume Element (RVE) model. After calculating the appropriate sample size based on margin of error and confidence level for initial void defects, a sample group of 5000 RVE models with initial void defects was generated. Dimensional reduction and density-based clustering analysis were conducted on the sample group to assess similarity, confirming and verifying that the sample group was unbiased. The validated sample analysis results were represented using a Weibull distribution, allowing them to be applied to the reliability analysis of composite structures.

• Journal of KIISE
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• v.42 no.7
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• pp.901-909
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• 2015

In this paper, to build a parallel corpus between Korean and English in Wikipedia. We proposed a method to find similar sentences based on language resources and topic modeling. We first applied language resources(Wiki-dictionary, numbers, and online dictionary in Daum) to match word sequentially. We construct the Wiki-dictionary using titles in Wikipedia. In order to take advantages of the Wikipedia, we used translation probability in the Wiki-dictionary for word matching. In addition, we improved the accuracy of sentence similarity measuring method by using word distribution based on topic modeling. In the experiment, a previous study showed 48.4% of F1-score with only language resources based on linear combination and 51.6% with the topic modeling considering entire word distributions additionally. However, our proposed methods with sequential matching added translation probability to language resources and achieved 9.9% (58.3%) better result than the previous study. When using the proposed sequential matching method of language resources and topic modeling after considering important word distributions, the proposed system achieved 7.5%(59.1%) better than the previous study.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.300-300
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• 2018

최근 우리나라는 봄철 지속적으로 가뭄이 발생하는 추세로 모니터링과 더불어 가뭄 피해를 경감할 수 있도록 가뭄해석 기법이 필요하다. 이를 위해 우선적으로 우리나라 실정에 적합한 가뭄지수를 산정하고, 개선을 통해 가뭄정보들이 수자원확보를 위한 관리와 정책에 활용되어야 한다. 이에 따라 본 연구에서는 국내 기존에 활용되고 있는 수문학적 가뭄지수인 개선된 지표수공급지수(MSWSI : Modified Surface Water Supply Index)를 선정하고 개선하였으며, 개선된 MSWSI를 이용하여 앙상블기법 기반의 확률론적 가뭄해석을 수행하였다. MSWSI의 개선에 있어서는 우선, 유역 내 공식적으로 수집되는 모든 수문기상인자를 조사하여 기존 MSWSI에서 적용한 강수량, 하천유량, 댐 유입량, 지하수량 4가지 인자와 사용 가능한 댐 저수위, 댐 방류량 인자를 추가하여 반영하였다. 또한 각 수문인자들에 대하여 인자별로 적합한 확률분포를 적용하였다. 또한 극심한 가뭄이 발생한 2006년과 2014년을 대상으로 비교 검토를 실시하고, 앙상블기반 확률론적 가뭄전망을 수행하고 검증하였다. 연구결과, 본 연구에서 개선한 MSWSI가 2006년과 2014년 발생한 가뭄현상을 더 잘 나타내는 것으로 분석되었다. 또한 실제 수문기상현상을 더욱 잘 반영하여 실제 가뭄과 유사한 가뭄결과로 분석되어, 개선된 MSWSI가 효용성이 있음을 확인하였다. 또한 앙상블 기반의 확률론적 가뭄전망 결과, 본 연구에서 개선한 MSWSI를 이용하였을 때 더 우수한 것으로 분석되었다. 대부분의 유역에서 실제 가뭄지수가 개선된 MSWSI를 이용한 가뭄전망 범위에 속하는 것으로 나타나, 본 연구에서 개선한 MSWSI를 활용한다면 보다 정확한 가뭄모니터링 수행이 가능하며, 가뭄전망의 정확성을 높일 것으로 판단된다.

• School Mathematics
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• v.11 no.3
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• pp.513-526
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• 2009

The purpose of this paper intuitively shows the exact and logical explanation of Independent Event and Dependent Event. In actual classrooms, teachers have difficulty in describing the connection between those events and real life. Some teachers have wrong perceptions on the definition of those events. For example, they may not realize exactly what P(B A)=P(B) means and may not explain intuitively the original meaning of why it is independent event. Also they believe that Independent Event and Dependent Event do not always match with real life. This paper, therefore, tries to prove intuitively the exact meanings of those events in the Verbal Form with some examples and it proves that those events exactly match with real life. It is expected that this paper will greatly contribute to the improvement of probability education.

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.563-577
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• 2017

As the uncertainty of precipitation increases due to climate change, seasonal forecasting and the use of weather forecasts become essential for efficient water resources management. In this study, the categorical probabilistic long-term forecasts implemented by KMA (Korea Meteorological Administration) since June 2014 was evaluated using assessment indicators of Hit Rate, Reliability Diagram, and Relative Operating Curve (ROC) and a technique for obtaining quantitative precipitation estimates based on probabilistic forecasts was proposed. The probabilistic long-term forecasts showed its maximum predictability of 48% and the quantified precipitation estimates were closely matched with actual observations; maximum correlation coefficient (R) in predictability evaluation for 100% accurate and actual weather forecasts were 0.98 and 0.71, respectively. A precipitation quantification approach utilizing probabilistic forecasts proposed in this study is expected to enable water management considering the uncertainty of precipitation. This method is also expected to be a useful tool for supporting decision-making in the long-term planning for water resources management and reservoir operations.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.67-77
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• 2003

Watermark detection has a crucial role in copyright protection and authentication for multimedia Because be the correlation -based algorithm which has widely been used in the watermark detection doesn't utilize the distributional characteristics of cover image to be marked, its performance is not optimum. So a new detection algorithm is proposed which is optimum for multiplicative watermark embedding. By relying on statistical decision method, the proposed method is derived according to the Bayes decision theory. Neyman Pearson criterion, and distribution of wavelet coefficients, thus Permitting to minimize the missed detection probability subject to a given false detection probability The superiority of the proposed method has been tested from a robustness perspective. The results confirm the superiority of the proposed technique over classical correlation -based method.

• The Journal of the Korea Contents Association
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• v.6 no.4
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• pp.63-68
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• 2006

For the almost co티am convergent series $S_n$ of independent random variables, by investigating the limiting behavior of the tail series, $T_n=S-S_{n-1}=\sum_{i=n}^{\infty}X_i$, the rate of convergence of the series $S_n$ to a random variable S is studied in this paper. More specifically, the equivalence between the tail series weak law of large numbers and a limit law is established for a quasi-monotone decreasing sequence, thereby extending a result of Previous work to the wider class of the norming constants.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1195-1200
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• 2019

This paper proposes a detection algorithm for group testing. Group testing is a problem of finding a very small number of defect samples out of a large number of samples, which is similar to the problem of Compressed Sensing. In this paper, we define a noiseless group testing and propose a probabilistic algorithm for detection of defective samples. The proposed algorithm is constructed such that the extrinsic probabilities between the input and output signals exchange with each other so that the posterior probability of the output signal is maximized. Then, defective samples are found in the group testing problem through a simulation on the detection algorithm. The simulation results for this study are compared with the lower bound in the information theory to see how much difference in failure probability over the input and output signal sizes.