• Title/Summary/Keyword: conditional average

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On the use of time-dependent success criteria within risk-informed analyses. Application to LONF-ATWS sequences in PWR reactors

  • Jorge Sanchez-Torrijos;Cesar Queral;Carlos Paris;Maria Jose Rebollo;Miguel Sanchez-Perea;Jose Maria Posada
    • Nuclear Engineering and Technology
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    • v.54 no.12
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    • pp.4601-4619
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    • 2022
  • The classical Probabilistic Safety Analysis (PSA) does not include any time dependence explicitly. However, the success criteria (SC) could evolve during the cycle for some initiating events. In that sense, there is a type of sequence in which this time-dependency is quite important, the family of Anticipated Transient without Scram (ATWS) sequences in Pressurized Water Reactors. Therefore, a new risk-informed approach is proposed in this paper, which makes it possible to obtain the time-dependent SC evolution of the safety functions affected by the Moderator Temperature Coefficient (MTC) value. Then, the evolution of the ATWS conditional core damage probability (CCDP) could be obtained using a PSA model. To quantify the CCDP, the average values of the time-dependent failure probabilities must be computed. Finally, the comparison between the CCDP obtained through the application of the classical PSA approach and the new one makes it possible to quantify the impact of time-dependence on the SC of the headers that this new risk-informed ATWS approach can provide.

Valuing the Water Quality Changes in Paldang Watershed: Using New Water Quality Classification Criteria and Indices (새로운 분류체계를 이용한 수질변화의 경제적 가치 추정)

  • Kim, Yong-Joo;Yoo, Young Seong
    • Environmental and Resource Economics Review
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    • v.17 no.4
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    • pp.875-901
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    • 2008
  • This article estimates the economic values of changes in water quality of the Paldang Watershed by using the Choice Experiment (CE). The conditional logit model estimation results show that a small improvement in water quality from the 'status quo' level to the level of 'very good' increases average household's monthly utility by 3,157 Won, whereas a water quality degradation down to the 'normal' level gives rise to an increase in the monthly average utility by 9,649 Won. The corresponding social gain and loss of water quality changes to the Metropolitan Area were thus estimated about 285 billion Won and 872 billion Won, respectively. This article seems meaningful in that it resorts to the new water ecosystem classification criteria and indices that are respondent-friendly. They help a CE study like this to overcome one of its critical weakness that the number and contents of attributes of a CE study can quickly add to the information overload problem, especially where the environmental good under investigation is hard for ordinary respondents to understand.

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Voice Personality Transformation Using a Probabilistic Method (확률적 방법을 이용한 음성 개성 변환)

  • Lee Ki-Seung
    • 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.

Estimation Method of User's Gameplay Skill Level through the Performance of Gameplay Status (게임플레이 상태의 성과를 통한 게임숙련도 평가방법)

  • Chang, Hee-Dong
    • Journal of Korea Game Society
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    • v.17 no.3
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    • pp.21-32
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    • 2017
  • Computer games must keep the user immersed for fun. According to the immersion theory, maintaining the user's immersive state requires a continuous balance of game skill level and game difficulty level This study proposes a game skill estimation method of 9th grade that can be applied to a casual action game that can assume a zero-sum game, and additionally proposed a difficulty guessing method. The proposed methods can be implemented quickly and easily because it is a method determining by conditional mathematical expressions. Experiments on the accuracy of the proposed methods for the customized Pac-Man game show that the accuracy of the skill level was 1.2 grade as the difference on the average and the accuracy of the game difficulty level was 1.81 grade the difference on the average. The results show that the proposed methods are accurate enough to be applied to casual action games satisfying the zero-sum condition.

A Hybrid Shadow Testing Scheme During Ray Tracing (광선추적 수행중 혼합 음영검사에 관한 연구)

  • Eo, Kil-Su;Kyung, Chong-Min
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.26 no.3
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    • pp.95-104
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    • 1989
  • This paper presents a new shadow testing acceleration scheme for ray tracing called Hybrid Shadow Testing (HST) based on a conditional switching between the conventinal shadow testing method and Crow's shadow volume method, where the shadow polygons as well as the object polygons are registered onto the corresponding cells under the 3-D space subdivision environment. Despite the preprocessing time for the generation and registration of the shadow polygons, the total shadow testing time of the proposed algorithm, HST was approximately 50% of that of the conventional shadow testing method for several examples while the total ray tracing time was typically reduced by 30% from the conventional approach. This due to the selective use of the shadow volume method with a compromise between the maximal utilisation of shadow's spatial coherency and minimising the computational overhead for checking ray intersections with the shadow polygons. A parameter, $N_{th}$ denoting the critical number of shadow polygons between successive reflection points was used as a guideline for switching the shadow testing scheme between the conventional method and shadow volume method. A method for calculating $N_{th}$ from such statistical data as the number of object polygons, average polygon size average peripheral length of the polygons was proposed, resulting in good agreement with the experimental results.

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RNN-LSTM Based Soil Moisture Estimation Using Terra MODIS NDVI and LST (Terra MODIS NDVI 및 LST 자료와 RNN-LSTM을 활용한 토양수분 산정)

  • Jang, Wonjin;Lee, Yonggwan;Lee, Jiwan;Kim, Seongjoon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.61 no.6
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    • pp.123-132
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    • 2019
  • This study is to estimate the spatial soil moisture using Terra MODIS (Moderate Resolution Imaging Spectroradiometer) satellite data and machine learning technique. Using the 3 years (2015~2017) data of MODIS 16 days composite NDVI (Normalized Difference Vegetation Index) and daily Land Surface Temperature (LST), ground measured precipitation and sunshine hour of KMA (Korea Meteorological Administration), the RDA (Rural Development Administration) 10 cm~30 cm average TDR (Time Domain Reflectometry) measured soil moisture at 78 locations was tested. For daily analysis, the missing values of MODIS LST by clouds were interpolated by conditional merging method using KMA surface temperature observation data, and the 16 days NDVI was linearly interpolated to 1 day interval. By applying the RNN-LSTM (Recurrent Neural Network-Long Short Term Memory) artificial neural network model, 70% of the total period was trained and the rest 30% period was verified. The results showed that the coefficient of determination ($R^2$), Root Mean Square Error (RMSE), and Nash-Sutcliffe Efficiency were 0.78, 2.76%, and 0.75 respectively. In average, the clay soil moisture was estimated well comparing with the other soil types of silt, loam, and sand. This is because the clay has the intrinsic physical property for having narrow range of soil moisture variation between field capacity and wilting point.

A Statistical Prediction Model of Speakers' Intentions in a Goal-Oriented Dialogue (목적지향 대화에서 화자 의도의 통계적 예측 모델)

  • Kim, Dong-Hyun;Kim, Hark-Soo;Seo, Jung-Yun
    • Journal of KIISE:Software and Applications
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    • v.35 no.9
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    • pp.554-561
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    • 2008
  • Prediction technique of user's intention can be used as a post-processing method for reducing the search space of an automatic speech recognizer. Prediction technique of system's intention can be used as a pre-processing method for generating a flexible sentence. To satisfy these practical needs, we propose a statistical model to predict speakers' intentions that are generalized into pairs of a speech act and a concept sequence. Contrary to the previous model using simple n-gram statistic of speech acts, the proposed model represents a dialogue history of a current utterance to a feature set with various linguistic levels (i.e. n-grams of speech act and a concept sequence pairs, clue words, and state information of a domain frame). Then, the proposed model predicts the intention of the next utterance by using the feature set as inputs of CRFs (Conditional Random Fields). In the experiment in a schedule management domain, The proposed model showed the precision of 76.25% on prediction of user's speech act and the precision of 64.21% on prediction of user's concept sequence. The proposed model also showed the precision of 88.11% on prediction of system's speech act and the Precision of 87.19% on prediction of system's concept sequence. In addition, the proposed model showed 29.32% higher average precision than the previous model.

Early diagnosis of jaw osteomyelitis by easy digitalized panoramic analysis

  • Park, Moo Soung;Eo, Mi Young;Myoung, Hoon;Kim, Soung Min;Lee, Jong Ho
    • Maxillofacial Plastic and Reconstructive Surgery
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    • v.41
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    • pp.6.1-6.10
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    • 2019
  • Background: Osteomyelitis is an intraosseous inflammatory disease characterized by progressive inflammatory osteoclasia and ossification. The use of quantitative analysis to assist interpretation of osteomyelitis is increasingly being considered. The objective of this study was to perform early diagnosis of osteomyelitis on digital panoramic radiographs using basic functions provided by picture archiving and communication system (PACS), a program used to show radiographic images. Methods: This study targeted a total of 95 patients whose symptoms were confirmed as osteomyelitis under clinical, radiologic, pathological diagnosis over 11 years from 2008 to 2017. Five categorized patients were osteoradionecrosis, bisphosphonate-related osteonecrosis of jaw (BRONJ, suppurative and sclerosing type), and bacterial osteomyelitis (suppurative and sclerosing type), and the control group was 117 randomly sampled. The photographic density in a certain area of the digital panoramic radiograph was determined and compared using the "measure area rectangle," one of the basic PACS functions in INFINITT PACS® (INFINITT Healthcare, Seoul, South Korea). A conditional inference tree, one type of decision making tree, was generated with the program R for statistical analysis with SPSS®. Results: In the conditional inference tree generated from the obtained data, cases where the difference in average value exceeded 54.49 and the difference in minimum value was less than 54.49 and greater than 12.81 and the difference in minimum value exceeded 39 were considered suspicious of osteomyelitis. From these results, the disease could be correctly classified with a probability of 88.1%. There was no difference in photographic density value of BRONJ and bacterial osteomyelitis; therefore, it was not possible to classify BRONJ and bacterial osteomyelitis by quantitative analysis of panoramic radiographs based on existing research. Conclusions: This study demonstrates that it is feasible to measure photographic density using a basic function in PACS and apply the data to assist in the diagnosis of osteomyelitis.

A Comparison and Analysis of the Levee Height Determination Methods in Korea and the USA (우리나라와 미국의 제방고 산정 기법에 대한 비교 분석)

  • Kang, Tae-Uk;Lee, Sang-Ho;Yu, Kwon-Kyu
    • Journal of Korea Water Resources Association
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    • v.44 no.6
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    • pp.497-510
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    • 2011
  • A levee height is determined by adding a deterministic freeboard to a flood water level in Korea. In the USA, a levee height is determined by choosing a value conditionally among the freeboard criteria and the levels resulted from a probabilistic method. The probabilistic method adopts a conditional non-exceedance probability (CNP) which is the probability that the target stage will not be exceeded given a specific flood event. The purpose of the study is to compare Korean criterion for levee height estimation with that of the USA. Levee heights were determined according to the above two criteria at twenty-five cross sections in five streams. The results show that Korean criterion on average yields levee heights 20 cm higher than those calculated by the criterion of the USA. The larger the flood discharges become, the higher the levee height differences are usually. It is caused by the freeboard estimation criterion of Korea that the larger design flood is, the higher freeboard is given. Korean criterion, however, resulted in lower levee heights for smaller streams than those by the criterion of the USA. To sum it up, the Korean levee height criteria can result in overestimation or underestimation depending on flood discharge amount, being compared with the criteria of the USA. The Korean freeboard especially needs to be increased for smaller flood discharges.

Yongdam Dam Watershed Flood Simulation Using GPM Satellite Data and KIMSTORM2 Distributed Storm Runoff Model (GPM위성 강우자료와 KIMSTORM2 분포형 유출모형을 이용한 용담댐 유역 홍수모의)

  • KIM, Se-Hoon;KIM, Jin-Uk;CHUNG, Jee-Hun;KIM, Seong-Joon
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.4
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    • pp.39-58
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    • 2019
  • This study performed the dam watershed storm runoff modeling using GPM(Global Precipitation Measurement) satellite rain and KIMSTORM2(KIneMatic wave STOrm Runoff Model 2) distributed model. For YongdamDam watershed(930㎢), three heavy rain events of 25th August 2014, 11th September 2017, and 26th June 2018 were selected and tested for 4 cases of spatial rainfalls such as (a) Kriging interpolated data using ground observed data at 7 stations, (b) original GPM data, (c) GPM corrected by CM(Conditional Merging), and GPM corrected by GDA(Geographical Differential Analysis). For the 4 kinds of data(Kriging, GPM, CM-GPM, and GDA-GPM), the KIMSTORM2 was calibrated respectively using the observed flood discharges at 3 water level gauge stations(Cheoncheon, Donghyang, and Yongdam) with parameters of initial soil moisture contents, stream Manning's roughness coefficient, and effective hydraulic conductivity. The total average Nash-Sutcliffe efficiency(NSE) for the 3 events and 3 stations was 0.94, 0.90, 0.94, and 0.94, determination coefficient(R2) was 0.96, 0.92, 0.97 and 0.96, the volume conservation index(VCI) was 1.03, 1.01, 1.03 and 1.02 for Kriging, GPM, CM-GPM, and GDA-GPM applications respectively. The CM-GPM and GDA-GPM showed better results than the original GPM application for peak runoff and runoff volume simulations, and they improved NSE, R2, and VCI results.