• Title/Summary/Keyword: Association probability

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The Role of Domain-specific Causal Mechanism and Domain-general Conditional Probability in Young Children's Causal Reasoning on Physics and Psychology (영역특정론과 영역일반론에 따른 유아의 인과추론 - 물리, 심리 영역을 중심으로 -)

  • Kim, Jihyun;Yi, Soon Hyung
    • Korean Journal of Child Studies
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    • v.29 no.5
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    • pp.243-269
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    • 2008
  • The role of domain-specific causal mechanism information and domain-general conditional probability in young children's causal reasoning on physics and psychology was investigated with the participation of 121 3-year-olds and 121 4-year-olds recruited from seven child care centers in Seoul, Kyonggi Province, and Busan. Children watched moving pictures on physical and psychological phenomena, and were asked to choose an appropriate cause and justify their choice. Results showed that young children's causal reasoning differed depending on domain-specific mechanism. In addition, their causal reasoning on physics and psychology differed by the developmental level of causal mechanism. The interaction of domain-specific mechanism and domain-general conditional probability influenced children's causal reasoning : evident conditional probability between domain-appropriate cause and effect helped children make more inferences based on domain-specific causal mechanism.

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Selection probability of multivariate regularization to identify pleiotropic variants in genetic association studies

  • Kim, Kipoong;Sun, Hokeun
    • Communications for Statistical Applications and Methods
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    • v.27 no.5
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    • pp.535-546
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    • 2020
  • In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

Evaluation of Probability Rainfalls Estimated from Non-Stationary Rainfall Frequency Analysis (비정상성 강우빈도해석법에 의한 확률강우량의 평가)

  • Lee, Chang-Hwan;Ahn, Jae-Hyun;Kim, Tae-Woong
    • Journal of Korea Water Resources Association
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    • v.43 no.2
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    • pp.187-199
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    • 2010
  • This study evaluated applicability and confidence of probability rainfalls estimated by the non-stationary rainfall frequency analysis which was recently developed. Using rainfall data at 4 sites which have an obvious increasing trend in observations, we estimated 3 type probability rainfalls; probability rainfalls from stationary rainfall frequency analysis using data from 1973-1997, probability rainfalls from stationary rainfall frequency analysis using data from 1973-2006, probability rainfalls from non-stationary rainfall frequency analysis assuming that the current year is 1997 and the target year is 2006. Based on the comparison of residuals from 3 probability rainfalls, the non-stationary rainfall frequency analysis provided more effective and well-directed estimates of probability rainfalls in the target year. Using Bootstrap resampling, this study also evaluated the parameter estimation methods for the non-stationary rainfall frequency analysis based on confidence intervals. The confidence interval length estimated by the maximum likelihood estimation (MLE) is narrower than the probability weighted moments (PWM). The results indicated that MLE provides more proper confidence than PWM for non-stationary probability rainfalls.

A Novel Algorithm of Joint Probability Data Association Based on Loss Function

  • Jiao, Hao;Liu, Yunxue;Yu, Hui;Li, Ke;Long, Feiyuan;Cui, Yingjie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2339-2355
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    • 2021
  • In this paper, a joint probabilistic data association algorithm based on loss function (LJPDA) is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously. Firstly, data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates. Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target, and the loss function, which reflects the cost of the new proposed data association algorithm, is defined. Moreover, the equation set of optimal contribution coefficient is given by minimizing the loss function, and the optimal contribution coefficient can be attained by using the Newton-Raphson method. In this way, the weighted value of each target can be achieved, and the data association among measurements and tracks can be realized. Finally, we compare performances of LJPDA proposed and joint probabilistic data association (JPDA) algorithm via numerical simulations, and much attention is paid on real-time performance and estimation error. Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.

Safety Analysis of Storm Sewer Using Probability of Failure and Multiple Failure Mode (파괴확률과 다중파괴유형을 이용한 우수관의 안전성 분석)

  • Kwon, Hyuk-Jae;Lee, Cheol-Eung
    • Journal of Korea Water Resources Association
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    • v.43 no.11
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    • pp.967-976
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    • 2010
  • AFDA (Approximate Full Distribution Approach) model of FORM (First-Order Reliability Model) which can quantitatively calculate the probability that storm sewer reach to performance limit state was developed in this study. It was defined as a failure if amount of inflow exceed the capacity of storm sewer. Manning's equation and rational equation were used to determine the capacity and inflow of reliability function. Furthermore, statistical characteristics and distribution for the random variables were analyzed as a reliability analysis. It was found that the statistical distribution for annual maximum rainfall intensity of 10 cities in Korea is matched well with Gumbel distribution. Reliability model developed in this study was applied to Y shaped storm sewer system to calculate the probability that storm sewer may exceed the performance limit state. Probability of failure according to diameter was calculated using Manning's equation. Especially, probability of failure of storm sewer in Mungyeong and Daejeon was calculated using rainfall intensity of 50-year return period. It was found that probability of failure can be significantly increased if diameter is decreased below the original diameter. Therefore, cleaning the debris in sewer pipes to maintain the original pipe diameter should be one of the best ways to reduce the probability of failure of storm sewer. In sewer system, two sewer pipes can flow into one sewer pipe. For this case, probability of system failure was calculated using multiple failure mode. Reliability model developed in this study can be applied to design, maintenance, management, and control of storm sewer system.

Prediction of the Probability of Job Loss due to Digitalization and Comparison by Industry: Using Machine Learning Methods

  • Park, Heedae;Lee, Kiyoul
    • Journal of Korea Trade
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    • v.25 no.5
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    • pp.110-128
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    • 2021
  • Purpose - The essential purpose of this study is to analyze the possibility of substitution of an individual job resulting from technological development represented by the 4th Industrial Resolution, considering the different effects of digital transformation on the labor market. Design/methodology - In order to estimate the substitution probability, this study used two data sets which the job characteristics data for individual occupations provided by KEIS and the information on occupational status of substitution provided by Frey and Osborne(2013). In total, 665 occupations were considered in this study. Of these, 80 occupations had data with labels of substitution status. The primary goal of estimation was to predict the degree of substitution for 607 of 665 occupations (excluding 58 with markers). It utilized three methods a principal component analysis, an unsupervised learning methodology of machine learning, and Ridge and Lasso from supervised learning methodology. After extracting significant variables based on the three methods, this study carried out logistics regression to estimate the probability of substitution for each occupation. Findings - The probability of substitution for other occupational groups did not significantly vary across individual models, and the rank order of the probabilities across occupational groups were similar across models. The mean of three methods of substitution probability was analyzed to be 45.3%. The highest value was obtained using the PCA method, and the lowest value was derived from the LASSO method. The average substitution probability of the trading industry was 45.1%, very similar to the overall average. Originality/value - This study has a significance in that it estimates the job substitution probability using various machine learning methods. The results of substitution probability estimation were compared by industry sector. In addition, This study attempts to compare between trade business and industry sector.

Development and Comparison of Data Mining-based Prediction Models of Building Fire Probability

  • Hong, Sung-gwan;Jeong, Seung Ryul
    • Journal of Internet Computing and Services
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    • v.19 no.6
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    • pp.101-112
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    • 2018
  • A lot of manpower and budgets are being used to prevent fires, and only a small portion of the data generated during this process is used for disaster prevention activities. This study develops a prediction model of fire occurrence probability based on data mining in order to more actively use these data for disaster prevention activities. For this purpose, variables for predicting fire occurrence probability of various buildings were selected and data of construction administrative system, national fire information system, and Korea Fire Insurance Association were collected and integrated data set was constructed. After appropriate data cleansing and preprocessing, various data mining methodologies such as artificial neural network, decision trees, SVM, and Naive Bayesian were used to develop a prediction model of the fire occurrence probability of buildings. The most accurate model among the derived models is Linear SVM model which shows 68.42% as experimental data and 63.54% as verification data and it is the best model to predict fire occurrence probability of buildings. As this study develops the prediction model which uses only the set values of the specific ranges, future studies may explore more opportunites to use various setting values not shown in this study.

A study on failure probability characteristic based on the reliability analysis according to the variation of boundary conditions (신뢰성 기반 쉴드터널의 경계조건 변화에 따른 파괴확률 특성에 관한 연구)

  • Gyu-Phil Lee;Young-Bin Park
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.25 no.6
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    • pp.447-458
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    • 2023
  • In this study, a comparison model considering the stochastic characteristics of the load and member resistance of the shield tunnel segment lining as well as the variability of the boundary condition was selected and reliability analysis was performed, and the adequacy of the limit state design was analyzed by calculating the probability of failure and reviewing the structural safety. For the analysis considering the probability characteristics of these ground constants, the ground spring coefficient was considered as the mean value by calculating the quantitative value by applying the Muirwood formula, and the coefficient of variation was selected based on the existing research data to review the models according to the change of ground boundary conditions. Through the structural analysis of these models and the reliability analysis using MCS technique, the failure probability and reliability index were calculated to examine the changes in the failure probability due to changes in ground boundary conditions.

Transmission Performance Analysis for OTAR in LINK16 communication system (LINK16 통신체계에서 무선 키 갱신을 위한 전송성능 분석)

  • Hong, Jin-Keun
    • Proceedings of the Korea Contents Association Conference
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    • 2004.11a
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    • pp.384-388
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    • 2004
  • In this paper, we analyses transmission performance of synchronization pattern for over the air rekeying in aerial tactical link of LINK16, when it is given by symbol error rate, in respect of pattern detection probability and false alarm probability.

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Investigation of Microbial Contamination and Working Environment in University Foodservices (대학급식소 작업시설과 환경의 미생물 오염도 분석 및 작업환경 실태조사)

  • Park, Soon-Hee;Moon, Hye-Kyung
    • Journal of the Korean Dietetic Association
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    • v.23 no.2
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    • pp.180-191
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    • 2017
  • The purpose of this study was to identity the probability of cross-contamination from the environment. For this, we examined foodservices at 20 universities/colleges for microbiological analysis of their working facilities and environment as well as their preventive equipment against cross-contamination. Seventy percent of the 20 foodservices were found to maintain one unified working area, which suggests high probability of contamination of food/utensils/equipment in the cooking area by pre-preparation or dish washing. According to the microbiological analysis, the hygiene acceptance ratio of working facilities in the clean zone was 70%, which was higher than the average 45% hygiene acceptance ratio of working facilities in the contamination operating zone. There was a significant difference in the total plate count (P<0.001) and coliform count (P<0.01), which demonstrates that work tables in the clean zone were in a good state compared to those in the contamination operating zone. In the contamination operating zone, refrigerator shelves had a high probability of cross-contamination. Regarding the floor surface and airborne microbes, cooking areas which should be maintained as clean zones had higher cross-contamination probability than those in the contamination operating zone. So corrective actions such as cleaning and sanitizing, keeping dry floors, lowered temperature and humidity, shoe disinfecting facilities, and checking concentrations, are necessary to manage floor surfaces and airborne microbes in the cooking area.