• Title/Summary/Keyword: 베이

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A Method of Selecting Test Metrics for Certifying Package Software using Bayesian Belief Network (베이지언 사용한 패키지 소프트웨어 인증을 위한 시험 메트릭 선택 기법)

  • Lee, Chong-Won;Lee, Byung-Jeong;Oh, Jae-Won;Wu, Chi-Su
    • Journal of KIISE:Software and Applications
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    • v.33 no.10
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    • pp.836-850
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    • 2006
  • Nowadays, due to the rapidly increasing number of package software products, quality test has been emphasized for package software products. When testing software products, one of the most important factors is to select metrics which form the bases for tests. In this paper, the types of package software are represented as characteristic vectors having probabilistic relationships with metrics. The characteristic vectors could be regarded as indicators of software type. To assign the metrics for each software type, the past test metrics are collected and analyzed. Using Bayesian belief network, the dependency relationship network of the characteristic vectors and metrics is constructed. The dependency relationship network is then used to find the proper metrics for the test of new package software products.

Landslide Susceptibility Analysis Using Bayesian Network and Semantic Technology (시맨틱 기술과 베이시안 네트워크를 이용한 산사태 취약성 분석)

  • Lee, Sang-Hoon
    • Journal of Korean Society for Geospatial Information Science
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    • v.18 no.4
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    • pp.61-69
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    • 2010
  • The collapse of a slope or cut embankment brings much damage to life and property. Accordingly, it is very important to analyze the spatial distribution by calculating the landslide susceptibility in the estimation of the risk of landslide occurrence. The heuristic, statistic, deterministic, and probabilistic methods have been introduced to make landslide susceptibility maps. In many cases, however, the reliability is low due to insufficient field data, and the qualitative experience and knowledge of experts could not be combined with the quantitative mechanical?analysis model in the existing methods. In this paper, new modeling method for a probabilistic landslide susceptibility analysis combined Bayesian Network with ontology model about experts' knowledge and spatial data was proposed. The ontology model, which was made using the reasoning engine, was automatically converted into the Bayesian Network structure. Through conditional probabilistic reasoning using the created Bayesian Network, landslide susceptibility with uncertainty was analyzed, and the results were described in maps, using GIS. The developed Bayesian Network was then applied to the test-site to verify its effect, and the result corresponded to the landslide traces boundary at 86.5% accuracy. We expect that general users will be able to make a landslide susceptibility analysis over a wide area without experts' help.

Mask Estimation Based on Band-Independent Bayesian Classifler for Missing-Feature Reconstruction (Missing-Feature 복구를 위한 대역 독립 방식의 베이시안 분류기 기반 마스크 예측 기법)

  • Kim Wooil;Stern Richard M.;Ko Hanseok
    • The Journal of the Acoustical Society of Korea
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    • v.25 no.2
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    • pp.78-87
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    • 2006
  • In this paper. we propose an effective mask estimation scheme for missing-feature reconstruction in order to achieve robust speech recognition under unknown noise environments. In the previous work. colored noise is used for training the mask classifer, which is generated from the entire frequency Partitioned signals. However it gives a limited performance under the restricted number of training database. To reflect the spectral events of more various background noise and improve the performance simultaneously. a new Bayesian classifier for mask estimation is proposed, which works independent of other frequency bands. In the proposed method, we employ the colored noise which is obtained by combining colored noises generated from each frequency band in order to reflect more various noise environments and mitigate the 'sparse' database problem. Combined with the cluster-based missing-feature reconstruction. the performance of the proposed method is evaluated on a task of noisy speech recognition. The results show that the proposed method has improved performance compared to the Previous method under white noise. car noise and background music conditions.

반입 컨테이너 무게를 고려한 재취급 최소화 장치 위치 결정 방안

  • 강재호;오명섭;류광렬;김갑환
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2004.11a
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    • pp.271-278
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    • 2004
  • 컨테이너 터미널에서 적하 작업을 수행할 때에는 선박의 안정성을 위하여 무거운 컨테이너들을 선박의 바닥쪽에 우선하여 배치한다. 그러므로 장치장(yard)에서 동일한 선박 베이(bay)에 선적할 컨테이너들을 무게가 무거운 순서로 효율적으로 반출할 수 있다면, 적하 계획의 수립과 수행일 수월해진다. 만일 장치장에서 적하를 위하여 지금 반출하여야 하는 컨테이너의 상단에 다른 컨테이너들이 장치되어 있다면, 부득이하게 위에 놓여 있는 컨테이너들을 임시로 옮겨야 하는데, 이러한 부가 작업을 재취급(rehandling)이라 한다. 채취급이 빈번히 발생하게 되면 적하 작업의 흐름은 차질을 빚게 되므로 재취급의 최소화는 작업 효율 측면에서 매우 중요하다. 본 논문에서는 컨테이너가 장치장에 반입되는 시점에 해당 컨테이너의 무게를 알 수 있다는 가정하에, 적하 작업을 위한 반출시 재취급이 적게 발생하도록 신규 반입된 컨테이너의 장치 위치를 결정하는 휴리스틱을 제안한다. 제안하는 휴리스틱은 각 스택(stack)별로 장치되어 있는 컨테이너들 중에서 자장 먼저 반출될 가장 무거운 컨테이너의 무게를 해당 스택의 대표 무게로 설정하고, 이를 신규 반입 컨테이너의 무게와 비교하여 장치 위치를 결정한다. 장치장 베이 하나로 시뮬레이션한 실험 결과 4단 6열 및 6단 9열의 장치장 베이 구조에서 임의의 위치에 신규 반입 컨테이너를 장치하는 방식에 비해 재취급 횟수를 1/5이하로 줄일 수 있음을 확인하였다

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Stochastic Fatigue Life Assesment based on Bayesian-inference (베이지언 추론에 기반한 확률론적 피로수명 평가)

  • Park, Myong-Jin;Kim, Yooil
    • Journal of the Society of Naval Architects of Korea
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    • v.56 no.2
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    • pp.161-167
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    • 2019
  • In general, fatigue analysis is performed by using deterministic model to estimate the optimal parameters. However, the deterministic model is difficult to clearly describe the physical phenomena of fatigue failure that contains many uncertainty factors. With regard to this, efforts have been made in this research to compare with the deterministic model and the stochastic models. Firstly, One deterministic S-N curve was derived from ordinary least squares technique and two P-S-N curves were estimated through Bayesian-linear regression model and Markov-Chain Monte Carlo simulation. Secondly, the distribution of Long-term fatigue damage and fatigue life were predicted by using the parameters obtained from the three methodologies and the long-term stress distribution.

Comparing the Impacts of Renewable Energy Policies on the Macroeconomy with Electricity Market Rigidities: A Bayesian DSGE Model (전력시장의 경직성에 따른 국가 재생에너지 정책이 거시경제에 미치는 영향 분석: 베이지언 DSGE 모형 접근)

  • Choi, Bongseok;Kim, Kihwan
    • Environmental and Resource Economics Review
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    • v.31 no.3
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    • pp.367-391
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    • 2022
  • We develop an energy-economy Bayesian DSGE model with the two sectors of electricity generations-traditional (fossil, nuclear) and renewable energy. Under imperfect substitutability between the two sectors, a technological shock on renewable energy sectors does not sufficient to facilitate energy conversion and reduce greenhouse gas emissions. Technology innovation on greenhouse gas emission reduction is also required. More importantly, sufficient investment should be derived by a well-functioning electricity market where electricity price plays a signal role in efficient allocation of resources. Indeed, market rigidities cause reduced consumption.